llama-1B/64_GPUS/dp-1_tp-8_pp-8_mbz-8/log.out

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START TIME: Sat Jul  6 09:34:44 UTC 2024
python3 version = Python 3.10.14
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M	examples/config_tiny_llama.py
M	examples/config_tiny_llama.yaml
M	examples/train_tiny_llama.sh
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Job status: RUNNING
[2024-07-06 09:34:46,978] torch.distributed.run: [WARNING] 
[2024-07-06 09:34:46,978] torch.distributed.run: [WARNING] *****************************************
[2024-07-06 09:34:46,978] torch.distributed.run: [WARNING] Setting OMP_NUM_THREADS environment variable for each process to be 1 in default, to avoid your system being overloaded, please further tune the variable for optimal performance in your application as needed. 
[2024-07-06 09:34:46,978] torch.distributed.run: [WARNING] *****************************************
[2024-07-06 09:34:46,984] torch.distributed.run: [WARNING] 
[2024-07-06 09:34:46,984] torch.distributed.run: [WARNING] *****************************************
[2024-07-06 09:34:46,984] torch.distributed.run: [WARNING] Setting OMP_NUM_THREADS environment variable for each process to be 1 in default, to avoid your system being overloaded, please further tune the variable for optimal performance in your application as needed. 
[2024-07-06 09:34:46,984] torch.distributed.run: [WARNING] *****************************************
[2024-07-06 09:34:46,984] torch.distributed.run: [WARNING] 
[2024-07-06 09:34:46,984] torch.distributed.run: [WARNING] *****************************************
[2024-07-06 09:34:46,984] torch.distributed.run: [WARNING] Setting OMP_NUM_THREADS environment variable for each process to be 1 in default, to avoid your system being overloaded, please further tune the variable for optimal performance in your application as needed. 
[2024-07-06 09:34:46,984] torch.distributed.run: [WARNING] *****************************************
[2024-07-06 09:34:46,996] torch.distributed.run: [WARNING] 
[2024-07-06 09:34:46,996] torch.distributed.run: [WARNING] *****************************************
[2024-07-06 09:34:46,996] torch.distributed.run: [WARNING] Setting OMP_NUM_THREADS environment variable for each process to be 1 in default, to avoid your system being overloaded, please further tune the variable for optimal performance in your application as needed. 
[2024-07-06 09:34:46,996] torch.distributed.run: [WARNING] *****************************************
[2024-07-06 09:34:47,022] torch.distributed.run: [WARNING] 
[2024-07-06 09:34:47,022] torch.distributed.run: [WARNING] *****************************************
[2024-07-06 09:34:47,022] torch.distributed.run: [WARNING] Setting OMP_NUM_THREADS environment variable for each process to be 1 in default, to avoid your system being overloaded, please further tune the variable for optimal performance in your application as needed. 
[2024-07-06 09:34:47,022] torch.distributed.run: [WARNING] *****************************************
[2024-07-06 09:34:47,022] torch.distributed.run: [WARNING] 
[2024-07-06 09:34:47,022] torch.distributed.run: [WARNING] *****************************************
[2024-07-06 09:34:47,022] torch.distributed.run: [WARNING] Setting OMP_NUM_THREADS environment variable for each process to be 1 in default, to avoid your system being overloaded, please further tune the variable for optimal performance in your application as needed. 
[2024-07-06 09:34:47,022] torch.distributed.run: [WARNING] *****************************************
[2024-07-06 09:34:47,027] torch.distributed.run: [WARNING] 
[2024-07-06 09:34:47,027] torch.distributed.run: [WARNING] *****************************************
[2024-07-06 09:34:47,027] torch.distributed.run: [WARNING] Setting OMP_NUM_THREADS environment variable for each process to be 1 in default, to avoid your system being overloaded, please further tune the variable for optimal performance in your application as needed. 
[2024-07-06 09:34:47,027] torch.distributed.run: [WARNING] *****************************************
[2024-07-06 09:34:47,048] torch.distributed.run: [WARNING] 
[2024-07-06 09:34:47,048] torch.distributed.run: [WARNING] *****************************************
[2024-07-06 09:34:47,048] torch.distributed.run: [WARNING] Setting OMP_NUM_THREADS environment variable for each process to be 1 in default, to avoid your system being overloaded, please further tune the variable for optimal performance in your application as needed. 
[2024-07-06 09:34:47,048] torch.distributed.run: [WARNING] *****************************************
[default0]:07/06/2024 09:35:06 [WARNING|DP=0|PP=0|TP=0|ip-26-0-160-103]: [Vocab Size Padding] Padded vocab (size: 50257) with 7 dummy tokens (new size: 50264)
[default0]:07/06/2024 09:35:06 [INFO|DP=0|PP=0|TP=0|ip-26-0-160-103]: Config:
[default0]:07/06/2024 09:35:06 [INFO|DP=0|PP=0|TP=0|ip-26-0-160-103]: Config(general=GeneralArgs(project='bench_cluster',
[default0]:07/06/2024 09:35:06 [INFO|DP=0|PP=0|TP=0|ip-26-0-160-103]:                            run='%date_%jobid',
[default0]:07/06/2024 09:35:06 [INFO|DP=0|PP=0|TP=0|ip-26-0-160-103]:                            seed=42,
[default0]:07/06/2024 09:35:06 [INFO|DP=0|PP=0|TP=0|ip-26-0-160-103]:                            step=None,
[default0]:07/06/2024 09:35:06 [INFO|DP=0|PP=0|TP=0|ip-26-0-160-103]:                            consumed_train_samples=None,
[default0]:07/06/2024 09:35:06 [INFO|DP=0|PP=0|TP=0|ip-26-0-160-103]:                            benchmark_csv_path=None,
[default0]:07/06/2024 09:35:06 [INFO|DP=0|PP=0|TP=0|ip-26-0-160-103]:                            ignore_sanity_checks=True),
[default0]:07/06/2024 09:35:06 [INFO|DP=0|PP=0|TP=0|ip-26-0-160-103]:        parallelism=ParallelismArgs(dp=1,
[default0]:07/06/2024 09:35:06 [INFO|DP=0|PP=0|TP=0|ip-26-0-160-103]:                                    pp=8,
[default0]:07/06/2024 09:35:06 [INFO|DP=0|PP=0|TP=0|ip-26-0-160-103]:                                    tp=8,
[default0]:07/06/2024 09:35:06 [INFO|DP=0|PP=0|TP=0|ip-26-0-160-103]:                                    pp_engine=<nanotron.parallel.pipeline_parallel.engine.AllForwardAllBackwardPipelineEngine object at 0x7fd22b3ec550>,
[default0]:07/06/2024 09:35:06 [INFO|DP=0|PP=0|TP=0|ip-26-0-160-103]:                                    tp_mode=<TensorParallelLinearMode.REDUCE_SCATTER: 2>,
[default0]:07/06/2024 09:35:06 [INFO|DP=0|PP=0|TP=0|ip-26-0-160-103]:                                    tp_linear_async_communication=False,
[default0]:07/06/2024 09:35:06 [INFO|DP=0|PP=0|TP=0|ip-26-0-160-103]:                                    expert_parallel_size=1),
[default0]:07/06/2024 09:35:06 [INFO|DP=0|PP=0|TP=0|ip-26-0-160-103]:        model=ModelArgs(model_config=LlamaConfig(bos_token_id=1,
[default0]:07/06/2024 09:35:06 [INFO|DP=0|PP=0|TP=0|ip-26-0-160-103]:                                                 eos_token_id=2,
[default0]:07/06/2024 09:35:06 [INFO|DP=0|PP=0|TP=0|ip-26-0-160-103]:                                                 hidden_act='silu',
[default0]:07/06/2024 09:35:06 [INFO|DP=0|PP=0|TP=0|ip-26-0-160-103]:                                                 hidden_size=2048,
[default0]:07/06/2024 09:35:06 [INFO|DP=0|PP=0|TP=0|ip-26-0-160-103]:                                                 initializer_range=0.02,
[default0]:07/06/2024 09:35:06 [INFO|DP=0|PP=0|TP=0|ip-26-0-160-103]:                                                 intermediate_size=4096,
[default0]:07/06/2024 09:35:06 [INFO|DP=0|PP=0|TP=0|ip-26-0-160-103]:                                                 is_llama_config=True,
[default0]:07/06/2024 09:35:06 [INFO|DP=0|PP=0|TP=0|ip-26-0-160-103]:                                                 max_position_embeddings=4096,
[default0]:07/06/2024 09:35:06 [INFO|DP=0|PP=0|TP=0|ip-26-0-160-103]:                                                 num_attention_heads=32,
[default0]:07/06/2024 09:35:06 [INFO|DP=0|PP=0|TP=0|ip-26-0-160-103]:                                                 num_hidden_layers=24,
[default0]:07/06/2024 09:35:06 [INFO|DP=0|PP=0|TP=0|ip-26-0-160-103]:                                                 num_key_value_heads=32,
[default0]:07/06/2024 09:35:06 [INFO|DP=0|PP=0|TP=0|ip-26-0-160-103]:                                                 pad_token_id=None,
[default0]:07/06/2024 09:35:06 [INFO|DP=0|PP=0|TP=0|ip-26-0-160-103]:                                                 pretraining_tp=1,
[default0]:07/06/2024 09:35:06 [INFO|DP=0|PP=0|TP=0|ip-26-0-160-103]:                                                 rms_norm_eps=1e-05,
[default0]:07/06/2024 09:35:06 [INFO|DP=0|PP=0|TP=0|ip-26-0-160-103]:                                                 rope_scaling=None,
[default0]:07/06/2024 09:35:06 [INFO|DP=0|PP=0|TP=0|ip-26-0-160-103]:                                                 rope_theta=10000.0,
[default0]:07/06/2024 09:35:06 [INFO|DP=0|PP=0|TP=0|ip-26-0-160-103]:                                                 tie_word_embeddings=True,
[default0]:07/06/2024 09:35:06 [INFO|DP=0|PP=0|TP=0|ip-26-0-160-103]:                                                 use_cache=True,
[default0]:07/06/2024 09:35:06 [INFO|DP=0|PP=0|TP=0|ip-26-0-160-103]:                                                 vocab_size=50264),
[default0]:07/06/2024 09:35:06 [INFO|DP=0|PP=0|TP=0|ip-26-0-160-103]:                        init_method=RandomInit(std=0.025),
[default0]:07/06/2024 09:35:06 [INFO|DP=0|PP=0|TP=0|ip-26-0-160-103]:                        dtype=torch.bfloat16,
[default0]:07/06/2024 09:35:06 [INFO|DP=0|PP=0|TP=0|ip-26-0-160-103]:                        make_vocab_size_divisible_by=1,
[default0]:07/06/2024 09:35:06 [INFO|DP=0|PP=0|TP=0|ip-26-0-160-103]:                        ddp_bucket_cap_mb=25),
[default0]:07/06/2024 09:35:06 [INFO|DP=0|PP=0|TP=0|ip-26-0-160-103]:        tokenizer=TokenizerArgs(tokenizer_name_or_path='openai-community/gpt2',
[default0]:07/06/2024 09:35:06 [INFO|DP=0|PP=0|TP=0|ip-26-0-160-103]:                                tokenizer_revision=None,
[default0]:07/06/2024 09:35:06 [INFO|DP=0|PP=0|TP=0|ip-26-0-160-103]:                                tokenizer_max_length=None),
[default0]:07/06/2024 09:35:06 [INFO|DP=0|PP=0|TP=0|ip-26-0-160-103]:        checkpoints=CheckpointsArgs(checkpoints_path=PosixPath('/dev/null'),
[default0]:07/06/2024 09:35:06 [INFO|DP=0|PP=0|TP=0|ip-26-0-160-103]:                                    checkpoint_interval=100000,
[default0]:07/06/2024 09:35:06 [INFO|DP=0|PP=0|TP=0|ip-26-0-160-103]:                                    save_initial_state=False,
[default0]:07/06/2024 09:35:06 [INFO|DP=0|PP=0|TP=0|ip-26-0-160-103]:                                    resume_checkpoint_path=None,
[default0]:07/06/2024 09:35:06 [INFO|DP=0|PP=0|TP=0|ip-26-0-160-103]:                                    checkpoints_path_is_shared_file_system=False),
[default0]:07/06/2024 09:35:06 [INFO|DP=0|PP=0|TP=0|ip-26-0-160-103]:        logging=LoggingArgs(log_level='info',
[default0]:07/06/2024 09:35:06 [INFO|DP=0|PP=0|TP=0|ip-26-0-160-103]:                            log_level_replica='info',
[default0]:07/06/2024 09:35:06 [INFO|DP=0|PP=0|TP=0|ip-26-0-160-103]:                            iteration_step_info_interval=1),
[default0]:07/06/2024 09:35:06 [INFO|DP=0|PP=0|TP=0|ip-26-0-160-103]:        tokens=TokensArgs(sequence_length=4096,
[default0]:07/06/2024 09:35:06 [INFO|DP=0|PP=0|TP=0|ip-26-0-160-103]:                          train_steps=20,
[default0]:07/06/2024 09:35:06 [INFO|DP=0|PP=0|TP=0|ip-26-0-160-103]:                          micro_batch_size=8,
[default0]:07/06/2024 09:35:06 [INFO|DP=0|PP=0|TP=0|ip-26-0-160-103]:                          batch_accumulation_per_replica=128,
[default0]:07/06/2024 09:35:06 [INFO|DP=0|PP=0|TP=0|ip-26-0-160-103]:                          val_check_interval=-1,
[default0]:07/06/2024 09:35:06 [INFO|DP=0|PP=0|TP=0|ip-26-0-160-103]:                          limit_val_batches=0,
[default0]:07/06/2024 09:35:06 [INFO|DP=0|PP=0|TP=0|ip-26-0-160-103]:                          limit_test_batches=0),
[default0]:07/06/2024 09:35:06 [INFO|DP=0|PP=0|TP=0|ip-26-0-160-103]:        optimizer=OptimizerArgs(optimizer_factory=AdamWOptimizerArgs(adam_eps=1e-08,
[default0]:07/06/2024 09:35:06 [INFO|DP=0|PP=0|TP=0|ip-26-0-160-103]:                                                                     adam_beta1=0.9,
[default0]:07/06/2024 09:35:06 [INFO|DP=0|PP=0|TP=0|ip-26-0-160-103]:                                                                     adam_beta2=0.95,
[default0]:07/06/2024 09:35:06 [INFO|DP=0|PP=0|TP=0|ip-26-0-160-103]:                                                                     torch_adam_is_fused=True,
[default0]:07/06/2024 09:35:06 [INFO|DP=0|PP=0|TP=0|ip-26-0-160-103]:                                                                     name='adamW'),
[default0]:07/06/2024 09:35:06 [INFO|DP=0|PP=0|TP=0|ip-26-0-160-103]:                                zero_stage=1,
[default0]:07/06/2024 09:35:06 [INFO|DP=0|PP=0|TP=0|ip-26-0-160-103]:                                weight_decay=0.01,
[default0]:07/06/2024 09:35:06 [INFO|DP=0|PP=0|TP=0|ip-26-0-160-103]:                                clip_grad=1.0,
[default0]:07/06/2024 09:35:06 [INFO|DP=0|PP=0|TP=0|ip-26-0-160-103]:                                accumulate_grad_in_fp32=True,
[default0]:07/06/2024 09:35:06 [INFO|DP=0|PP=0|TP=0|ip-26-0-160-103]:                                learning_rate_scheduler=LRSchedulerArgs(learning_rate=0.0001,
[default0]:07/06/2024 09:35:06 [INFO|DP=0|PP=0|TP=0|ip-26-0-160-103]:                                                                        lr_warmup_steps=1,
[default0]:07/06/2024 09:35:06 [INFO|DP=0|PP=0|TP=0|ip-26-0-160-103]:                                                                        lr_warmup_style='linear',
[default0]:07/06/2024 09:35:06 [INFO|DP=0|PP=0|TP=0|ip-26-0-160-103]:                                                                        lr_decay_style='linear',
[default0]:07/06/2024 09:35:06 [INFO|DP=0|PP=0|TP=0|ip-26-0-160-103]:                                                                        lr_decay_steps=19,
[default0]:07/06/2024 09:35:06 [INFO|DP=0|PP=0|TP=0|ip-26-0-160-103]:                                                                        lr_decay_starting_step=None,
[default0]:07/06/2024 09:35:06 [INFO|DP=0|PP=0|TP=0|ip-26-0-160-103]:                                                                        min_decay_lr=1e-05)),
[default0]:07/06/2024 09:35:06 [INFO|DP=0|PP=0|TP=0|ip-26-0-160-103]:        data_stages=[DatasetStageArgs(name='Training Stage',
[default0]:07/06/2024 09:35:06 [INFO|DP=0|PP=0|TP=0|ip-26-0-160-103]:                                      start_training_step=1,
[default0]:07/06/2024 09:35:06 [INFO|DP=0|PP=0|TP=0|ip-26-0-160-103]:                                      data=DataArgs(dataset=PretrainDatasetsArgs(hf_dataset_or_datasets='roneneldan/TinyStories',
[default0]:07/06/2024 09:35:06 [INFO|DP=0|PP=0|TP=0|ip-26-0-160-103]:                                                                                 hf_dataset_splits='train',
[default0]:07/06/2024 09:35:06 [INFO|DP=0|PP=0|TP=0|ip-26-0-160-103]:                                                                                 hf_dataset_config_name=None,
[default0]:07/06/2024 09:35:06 [INFO|DP=0|PP=0|TP=0|ip-26-0-160-103]:                                                                                 dataset_processing_num_proc_per_process=64,
[default0]:07/06/2024 09:35:06 [INFO|DP=0|PP=0|TP=0|ip-26-0-160-103]:                                                                                 dataset_overwrite_cache=False,
[default0]:07/06/2024 09:35:06 [INFO|DP=0|PP=0|TP=0|ip-26-0-160-103]:                                                                                 text_column_name='text'),
[default0]:07/06/2024 09:35:06 [INFO|DP=0|PP=0|TP=0|ip-26-0-160-103]:                                                    seed=42,
[default0]:07/06/2024 09:35:06 [INFO|DP=0|PP=0|TP=0|ip-26-0-160-103]:                                                    num_loading_workers=0))],
[default0]:07/06/2024 09:35:06 [INFO|DP=0|PP=0|TP=0|ip-26-0-160-103]:        profiler=ProfilerArgs(profiler_export_path=PosixPath('/fsx/ferdinandmom/ferdinand-hf/bench_cluster/results/llama-1B/64_GPUS/dp-1_tp-8_pp-8_mbz-8')),
[default0]:07/06/2024 09:35:06 [INFO|DP=0|PP=0|TP=0|ip-26-0-160-103]:        lighteval=None)
[default0]:07/06/2024 09:35:06 [INFO|DP=0|PP=0|TP=0|ip-26-0-160-103]: Model Config:
[default0]:07/06/2024 09:35:06 [INFO|DP=0|PP=0|TP=0|ip-26-0-160-103]: LlamaConfig(bos_token_id=1,
[default0]:07/06/2024 09:35:06 [INFO|DP=0|PP=0|TP=0|ip-26-0-160-103]:             eos_token_id=2,
[default0]:07/06/2024 09:35:06 [INFO|DP=0|PP=0|TP=0|ip-26-0-160-103]:             hidden_act='silu',
[default0]:07/06/2024 09:35:06 [INFO|DP=0|PP=0|TP=0|ip-26-0-160-103]:             hidden_size=2048,
[default0]:07/06/2024 09:35:06 [INFO|DP=0|PP=0|TP=0|ip-26-0-160-103]:             initializer_range=0.02,
[default0]:07/06/2024 09:35:06 [INFO|DP=0|PP=0|TP=0|ip-26-0-160-103]:             intermediate_size=4096,
[default0]:07/06/2024 09:35:06 [INFO|DP=0|PP=0|TP=0|ip-26-0-160-103]:             is_llama_config=True,
[default0]:07/06/2024 09:35:06 [INFO|DP=0|PP=0|TP=0|ip-26-0-160-103]:             max_position_embeddings=4096,
[default0]:07/06/2024 09:35:06 [INFO|DP=0|PP=0|TP=0|ip-26-0-160-103]:             num_attention_heads=32,
[default0]:07/06/2024 09:35:06 [INFO|DP=0|PP=0|TP=0|ip-26-0-160-103]:             num_hidden_layers=24,
[default0]:07/06/2024 09:35:06 [INFO|DP=0|PP=0|TP=0|ip-26-0-160-103]:             num_key_value_heads=32,
[default0]:07/06/2024 09:35:06 [INFO|DP=0|PP=0|TP=0|ip-26-0-160-103]:             pad_token_id=None,
[default0]:07/06/2024 09:35:06 [INFO|DP=0|PP=0|TP=0|ip-26-0-160-103]:             pretraining_tp=1,
[default0]:07/06/2024 09:35:06 [INFO|DP=0|PP=0|TP=0|ip-26-0-160-103]:             rms_norm_eps=1e-05,
[default0]:07/06/2024 09:35:06 [INFO|DP=0|PP=0|TP=0|ip-26-0-160-103]:             rope_scaling=None,
[default0]:07/06/2024 09:35:06 [INFO|DP=0|PP=0|TP=0|ip-26-0-160-103]:             rope_theta=10000.0,
[default0]:07/06/2024 09:35:06 [INFO|DP=0|PP=0|TP=0|ip-26-0-160-103]:             tie_word_embeddings=True,
[default0]:07/06/2024 09:35:06 [INFO|DP=0|PP=0|TP=0|ip-26-0-160-103]:             use_cache=True,
[default0]:07/06/2024 09:35:06 [INFO|DP=0|PP=0|TP=0|ip-26-0-160-103]:             vocab_size=50264)
[default0]:07/06/2024 09:35:06 [INFO|DP=0|PP=0|TP=0|ip-26-0-160-103]: Building model..
[default0]:07/06/2024 09:35:06 [INFO|DP=0|PP=0|TP=0|ip-26-0-160-103]: Setting PP block ranks...
[default0]:07/06/2024 09:35:24 [INFO|DP=0|PP=7|TP=0|ip-26-0-172-147]: Local number of parameters: 12.9M (24.55MiB)
[default0]:07/06/2024 09:35:24 [INFO|DP=0|PP=7|TP=0|ip-26-0-172-147]: [After model building] Memory usage: 24.56MiB. Peak allocated: 24.58MiB Peak reserved: 28.00MiB
[default0]:07/06/2024 09:35:24 [INFO|DP=0|PP=7|TP=0|ip-26-0-172-147]: No checkpoint path provided.
[default6]:07/06/2024 09:35:24 [INFO|DP=0|PP=7|TP=6|ip-26-0-172-147]: Local number of parameters: 12.9M (24.55MiB)
[default6]:07/06/2024 09:35:24 [INFO|DP=0|PP=7|TP=6|ip-26-0-172-147]: [After model building] Memory usage: 24.56MiB. Peak allocated: 24.58MiB Peak reserved: 28.00MiB
[default6]:07/06/2024 09:35:24 [INFO|DP=0|PP=7|TP=6|ip-26-0-172-147]: No checkpoint path provided.
[default4]:07/06/2024 09:35:24 [INFO|DP=0|PP=3|TP=4|ip-26-0-163-58]: Local number of parameters: 21M (40.03MiB)
[default4]:07/06/2024 09:35:24 [INFO|DP=0|PP=3|TP=4|ip-26-0-163-58]: [After model building] Memory usage: 44.04MiB. Peak allocated: 46.07MiB Peak reserved: 52.00MiB
[default4]:07/06/2024 09:35:24 [INFO|DP=0|PP=3|TP=4|ip-26-0-163-58]: No checkpoint path provided.
[default3]:07/06/2024 09:35:24 [INFO|DP=0|PP=3|TP=3|ip-26-0-163-58]: Local number of parameters: 21M (40.03MiB)
[default3]:07/06/2024 09:35:24 [INFO|DP=0|PP=3|TP=3|ip-26-0-163-58]: [After model building] Memory usage: 44.04MiB. Peak allocated: 46.07MiB Peak reserved: 52.00MiB
[default3]:07/06/2024 09:35:24 [INFO|DP=0|PP=3|TP=3|ip-26-0-163-58]: No checkpoint path provided.
[default2]:07/06/2024 09:35:24 [INFO|DP=0|PP=7|TP=2|ip-26-0-172-147]: Local number of parameters: 12.9M (24.55MiB)
[default0]:07/06/2024 09:35:24 [INFO|DP=0|PP=2|TP=0|ip-26-0-163-147]: Local number of parameters: 15.7M (30.02MiB)
[default0]:07/06/2024 09:35:24 [INFO|DP=0|PP=2|TP=0|ip-26-0-163-147]: [After model building] Memory usage: 33.03MiB. Peak allocated: 35.06MiB Peak reserved: 50.00MiB
[default0]:07/06/2024 09:35:24 [INFO|DP=0|PP=2|TP=0|ip-26-0-163-147]: No checkpoint path provided.
[default0]:07/06/2024 09:35:24 [INFO|DP=0|PP=3|TP=0|ip-26-0-163-58]: Local number of parameters: 21M (40.03MiB)
[default0]:07/06/2024 09:35:24 [INFO|DP=0|PP=3|TP=0|ip-26-0-163-58]: [After model building] Memory usage: 44.04MiB. Peak allocated: 46.07MiB Peak reserved: 52.00MiB
[default0]:07/06/2024 09:35:24 [INFO|DP=0|PP=3|TP=0|ip-26-0-163-58]: No checkpoint path provided.
[default2]:07/06/2024 09:35:24 [INFO|DP=0|PP=7|TP=2|ip-26-0-172-147]: [After model building] Memory usage: 24.56MiB. Peak allocated: 24.58MiB Peak reserved: 28.00MiB
[default5]:07/06/2024 09:35:24 [INFO|DP=0|PP=3|TP=5|ip-26-0-163-58]: Local number of parameters: 21M (40.03MiB)
[default5]:07/06/2024 09:35:24 [INFO|DP=0|PP=3|TP=5|ip-26-0-163-58]: [After model building] Memory usage: 44.04MiB. Peak allocated: 46.07MiB Peak reserved: 52.00MiB
[default5]:07/06/2024 09:35:24 [INFO|DP=0|PP=3|TP=5|ip-26-0-163-58]: No checkpoint path provided.
[default2]:07/06/2024 09:35:24 [INFO|DP=0|PP=7|TP=2|ip-26-0-172-147]: No checkpoint path provided.
[default0]:07/06/2024 09:35:24 [INFO|DP=0|PP=6|TP=0|ip-26-0-172-142]: Local number of parameters: 21M (40.03MiB)
[default0]:07/06/2024 09:35:24 [INFO|DP=0|PP=6|TP=0|ip-26-0-172-142]: [After model building] Memory usage: 44.04MiB. Peak allocated: 46.07MiB Peak reserved: 52.00MiB
[default0]:07/06/2024 09:35:24 [INFO|DP=0|PP=6|TP=0|ip-26-0-172-142]: No checkpoint path provided.
[default7]:07/06/2024 09:35:24 [INFO|DP=0|PP=3|TP=7|ip-26-0-163-58]: Local number of parameters: 21M (40.03MiB)
[default3]:07/06/2024 09:35:24 [INFO|DP=0|PP=7|TP=3|ip-26-0-172-147]: Local number of parameters: 12.9M (24.55MiB)
[default7]:07/06/2024 09:35:24 [INFO|DP=0|PP=3|TP=7|ip-26-0-163-58]: [After model building] Memory usage: 44.04MiB. Peak allocated: 46.07MiB Peak reserved: 52.00MiB
[default3]:07/06/2024 09:35:24 [INFO|DP=0|PP=7|TP=3|ip-26-0-172-147]: [After model building] Memory usage: 24.56MiB. Peak allocated: 24.58MiB Peak reserved: 28.00MiB
[default7]:07/06/2024 09:35:24 [INFO|DP=0|PP=3|TP=7|ip-26-0-163-58]: No checkpoint path provided.
[default6]:07/06/2024 09:35:24 [INFO|DP=0|PP=3|TP=6|ip-26-0-163-58]: Local number of parameters: 21M (40.03MiB)
[default7]:07/06/2024 09:35:24 [INFO|DP=0|PP=7|TP=7|ip-26-0-172-147]: Local number of parameters: 12.9M (24.55MiB)
[default6]:07/06/2024 09:35:24 [INFO|DP=0|PP=3|TP=6|ip-26-0-163-58]: [After model building] Memory usage: 44.04MiB. Peak allocated: 46.07MiB Peak reserved: 52.00MiB
[default6]:07/06/2024 09:35:24 [INFO|DP=0|PP=3|TP=6|ip-26-0-163-58]: No checkpoint path provided.
[default7]:07/06/2024 09:35:24 [INFO|DP=0|PP=7|TP=7|ip-26-0-172-147]: [After model building] Memory usage: 24.56MiB. Peak allocated: 24.58MiB Peak reserved: 28.00MiB
[default3]:07/06/2024 09:35:24 [INFO|DP=0|PP=7|TP=3|ip-26-0-172-147]: No checkpoint path provided.
[default6]:07/06/2024 09:35:24 [INFO|DP=0|PP=1|TP=6|ip-26-0-161-138]: Local number of parameters: 15.7M (30.02MiB)
[default0]:07/06/2024 09:35:24 [INFO|DP=0|PP=1|TP=0|ip-26-0-161-138]: Local number of parameters: 15.7M (30.02MiB)
[default1]:07/06/2024 09:35:24 [INFO|DP=0|PP=3|TP=1|ip-26-0-163-58]: Local number of parameters: 21M (40.03MiB)
[default1]:07/06/2024 09:35:24 [INFO|DP=0|PP=3|TP=1|ip-26-0-163-58]: [After model building] Memory usage: 44.04MiB. Peak allocated: 46.07MiB Peak reserved: 52.00MiB
[default1]:07/06/2024 09:35:24 [INFO|DP=0|PP=3|TP=1|ip-26-0-163-58]: No checkpoint path provided.
[default7]:07/06/2024 09:35:24 [INFO|DP=0|PP=7|TP=7|ip-26-0-172-147]: No checkpoint path provided.
[default6]:07/06/2024 09:35:24 [INFO|DP=0|PP=1|TP=6|ip-26-0-161-138]: [After model building] Memory usage: 33.03MiB. Peak allocated: 35.06MiB Peak reserved: 50.00MiB
[default2]:07/06/2024 09:35:24 [INFO|DP=0|PP=3|TP=2|ip-26-0-163-58]: Local number of parameters: 21M (40.03MiB)
[default1]:07/06/2024 09:35:24 [INFO|DP=0|PP=7|TP=1|ip-26-0-172-147]: Local number of parameters: 12.9M (24.55MiB)
[default1]:07/06/2024 09:35:24 [INFO|DP=0|PP=7|TP=1|ip-26-0-172-147]: [After model building] Memory usage: 24.56MiB. Peak allocated: 24.58MiB Peak reserved: 28.00MiB
[default3]:07/06/2024 09:35:24 [INFO|DP=0|PP=4|TP=3|ip-26-0-165-213]: Local number of parameters: 15.7M (30.02MiB)
[default3]:07/06/2024 09:35:24 [INFO|DP=0|PP=4|TP=3|ip-26-0-165-213]: [After model building] Memory usage: 33.03MiB. Peak allocated: 35.06MiB Peak reserved: 50.00MiB
[default1]:07/06/2024 09:35:24 [INFO|DP=0|PP=4|TP=1|ip-26-0-165-213]: Local number of parameters: 15.7M (30.02MiB)
[default1]:07/06/2024 09:35:24 [INFO|DP=0|PP=4|TP=1|ip-26-0-165-213]: [After model building] Memory usage: 33.03MiB. Peak allocated: 35.06MiB Peak reserved: 50.00MiB
[default3]:07/06/2024 09:35:24 [INFO|DP=0|PP=4|TP=3|ip-26-0-165-213]: No checkpoint path provided.
[default6]:07/06/2024 09:35:24 [INFO|DP=0|PP=1|TP=6|ip-26-0-161-138]: No checkpoint path provided.
[default0]:07/06/2024 09:35:24 [INFO|DP=0|PP=1|TP=0|ip-26-0-161-138]: [After model building] Memory usage: 33.03MiB. Peak allocated: 35.06MiB Peak reserved: 50.00MiB
[default0]:07/06/2024 09:35:24 [INFO|DP=0|PP=1|TP=0|ip-26-0-161-138]: No checkpoint path provided.
[default2]:07/06/2024 09:35:24 [INFO|DP=0|PP=3|TP=2|ip-26-0-163-58]: [After model building] Memory usage: 44.04MiB. Peak allocated: 46.07MiB Peak reserved: 52.00MiB
[default2]:07/06/2024 09:35:24 [INFO|DP=0|PP=3|TP=2|ip-26-0-163-58]: No checkpoint path provided.
[default1]:07/06/2024 09:35:24 [INFO|DP=0|PP=7|TP=1|ip-26-0-172-147]: No checkpoint path provided.
[default4]:07/06/2024 09:35:24 [INFO|DP=0|PP=6|TP=4|ip-26-0-172-142]: Local number of parameters: 21M (40.03MiB)
[default1]:07/06/2024 09:35:24 [INFO|DP=0|PP=2|TP=1|ip-26-0-163-147]: Local number of parameters: 15.7M (30.02MiB)
[default1]:07/06/2024 09:35:24 [INFO|DP=0|PP=2|TP=1|ip-26-0-163-147]: [After model building] Memory usage: 33.03MiB. Peak allocated: 35.06MiB Peak reserved: 50.00MiB
[default1]:07/06/2024 09:35:24 [INFO|DP=0|PP=4|TP=1|ip-26-0-165-213]: No checkpoint path provided.
[default4]:07/06/2024 09:35:24 [INFO|DP=0|PP=1|TP=4|ip-26-0-161-138]: Local number of parameters: 15.7M (30.02MiB)
[default4]:07/06/2024 09:35:24 [INFO|DP=0|PP=1|TP=4|ip-26-0-161-138]: [After model building] Memory usage: 33.03MiB. Peak allocated: 35.06MiB Peak reserved: 50.00MiB
[default4]:07/06/2024 09:35:24 [INFO|DP=0|PP=1|TP=4|ip-26-0-161-138]: No checkpoint path provided.
[default5]:07/06/2024 09:35:24 [INFO|DP=0|PP=7|TP=5|ip-26-0-172-147]: Local number of parameters: 12.9M (24.55MiB)
[default5]:07/06/2024 09:35:24 [INFO|DP=0|PP=7|TP=5|ip-26-0-172-147]: [After model building] Memory usage: 24.56MiB. Peak allocated: 24.58MiB Peak reserved: 28.00MiB
[default5]:07/06/2024 09:35:24 [INFO|DP=0|PP=7|TP=5|ip-26-0-172-147]: No checkpoint path provided.
[default1]:07/06/2024 09:35:24 [INFO|DP=0|PP=6|TP=1|ip-26-0-172-142]: Local number of parameters: 21M (40.03MiB)
[default1]:07/06/2024 09:35:24 [INFO|DP=0|PP=2|TP=1|ip-26-0-163-147]: No checkpoint path provided.
[default6]:07/06/2024 09:35:24 [INFO|DP=0|PP=4|TP=6|ip-26-0-165-213]: Local number of parameters: 15.7M (30.02MiB)
[default6]:07/06/2024 09:35:24 [INFO|DP=0|PP=4|TP=6|ip-26-0-165-213]: [After model building] Memory usage: 33.03MiB. Peak allocated: 35.06MiB Peak reserved: 50.00MiB
[default6]:07/06/2024 09:35:24 [INFO|DP=0|PP=4|TP=6|ip-26-0-165-213]: No checkpoint path provided.
[default4]:07/06/2024 09:35:24 [INFO|DP=0|PP=7|TP=4|ip-26-0-172-147]: Local number of parameters: 12.9M (24.55MiB)
[default1]:07/06/2024 09:35:24 [INFO|DP=0|PP=6|TP=1|ip-26-0-172-142]: [After model building] Memory usage: 44.04MiB. Peak allocated: 46.07MiB Peak reserved: 52.00MiB
[default1]:07/06/2024 09:35:24 [INFO|DP=0|PP=6|TP=1|ip-26-0-172-142]: No checkpoint path provided.
[default6]:07/06/2024 09:35:24 [INFO|DP=0|PP=2|TP=6|ip-26-0-163-147]: Local number of parameters: 15.7M (30.02MiB)
[default5]:07/06/2024 09:35:24 [INFO|DP=0|PP=4|TP=5|ip-26-0-165-213]: Local number of parameters: 15.7M (30.02MiB)
[default3]:07/06/2024 09:35:24 [INFO|DP=0|PP=1|TP=3|ip-26-0-161-138]: Local number of parameters: 15.7M (30.02MiB)
[default4]:07/06/2024 09:35:24 [INFO|DP=0|PP=7|TP=4|ip-26-0-172-147]: [After model building] Memory usage: 24.56MiB. Peak allocated: 24.58MiB Peak reserved: 28.00MiB
[default4]:07/06/2024 09:35:24 [INFO|DP=0|PP=7|TP=4|ip-26-0-172-147]: No checkpoint path provided.
[default4]:07/06/2024 09:35:24 [INFO|DP=0|PP=6|TP=4|ip-26-0-172-142]: [After model building] Memory usage: 44.04MiB. Peak allocated: 46.07MiB Peak reserved: 52.00MiB
[default4]:07/06/2024 09:35:24 [INFO|DP=0|PP=6|TP=4|ip-26-0-172-142]: No checkpoint path provided.
[default6]:07/06/2024 09:35:24 [INFO|DP=0|PP=2|TP=6|ip-26-0-163-147]: [After model building] Memory usage: 33.03MiB. Peak allocated: 35.06MiB Peak reserved: 50.00MiB
[default6]:07/06/2024 09:35:24 [INFO|DP=0|PP=2|TP=6|ip-26-0-163-147]: No checkpoint path provided.
[default0]:07/06/2024 09:35:24 [INFO|DP=0|PP=4|TP=0|ip-26-0-165-213]: Local number of parameters: 15.7M (30.02MiB)
[default3]:07/06/2024 09:35:24 [INFO|DP=0|PP=1|TP=3|ip-26-0-161-138]: [After model building] Memory usage: 33.03MiB. Peak allocated: 35.06MiB Peak reserved: 50.00MiB
[default5]:07/06/2024 09:35:24 [INFO|DP=0|PP=6|TP=5|ip-26-0-172-142]: Local number of parameters: 21M (40.03MiB)
[default5]:07/06/2024 09:35:24 [INFO|DP=0|PP=6|TP=5|ip-26-0-172-142]: [After model building] Memory usage: 44.04MiB. Peak allocated: 46.07MiB Peak reserved: 52.00MiB
[default5]:07/06/2024 09:35:24 [INFO|DP=0|PP=6|TP=5|ip-26-0-172-142]: No checkpoint path provided.
[default2]:07/06/2024 09:35:24 [INFO|DP=0|PP=2|TP=2|ip-26-0-163-147]: Local number of parameters: 15.7M (30.02MiB)
[default2]:07/06/2024 09:35:24 [INFO|DP=0|PP=2|TP=2|ip-26-0-163-147]: [After model building] Memory usage: 33.03MiB. Peak allocated: 35.06MiB Peak reserved: 50.00MiB
[default2]:07/06/2024 09:35:24 [INFO|DP=0|PP=2|TP=2|ip-26-0-163-147]: No checkpoint path provided.
[default5]:07/06/2024 09:35:24 [INFO|DP=0|PP=4|TP=5|ip-26-0-165-213]: [After model building] Memory usage: 33.03MiB. Peak allocated: 35.06MiB Peak reserved: 50.00MiB
[default3]:07/06/2024 09:35:24 [INFO|DP=0|PP=1|TP=3|ip-26-0-161-138]: No checkpoint path provided.
[default6]:07/06/2024 09:35:24 [INFO|DP=0|PP=6|TP=6|ip-26-0-172-142]: Local number of parameters: 21M (40.03MiB)
[default6]:07/06/2024 09:35:24 [INFO|DP=0|PP=6|TP=6|ip-26-0-172-142]: [After model building] Memory usage: 44.04MiB. Peak allocated: 46.07MiB Peak reserved: 52.00MiB
[default6]:07/06/2024 09:35:24 [INFO|DP=0|PP=6|TP=6|ip-26-0-172-142]: No checkpoint path provided.
[default3]:07/06/2024 09:35:24 [INFO|DP=0|PP=2|TP=3|ip-26-0-163-147]: Local number of parameters: 15.7M (30.02MiB)
[default5]:07/06/2024 09:35:24 [INFO|DP=0|PP=4|TP=5|ip-26-0-165-213]: No checkpoint path provided.
[default0]:07/06/2024 09:35:24 [INFO|DP=0|PP=4|TP=0|ip-26-0-165-213]: [After model building] Memory usage: 33.03MiB. Peak allocated: 35.06MiB Peak reserved: 50.00MiB
[default0]:07/06/2024 09:35:24 [INFO|DP=0|PP=4|TP=0|ip-26-0-165-213]: No checkpoint path provided.
[default5]:07/06/2024 09:35:24 [INFO|DP=0|PP=1|TP=5|ip-26-0-161-138]: Local number of parameters: 15.7M (30.02MiB)
[default5]:07/06/2024 09:35:24 [INFO|DP=0|PP=1|TP=5|ip-26-0-161-138]: [After model building] Memory usage: 33.03MiB. Peak allocated: 35.06MiB Peak reserved: 50.00MiB
[default7]:07/06/2024 09:35:24 [INFO|DP=0|PP=6|TP=7|ip-26-0-172-142]: Local number of parameters: 21M (40.03MiB)
[default7]:07/06/2024 09:35:24 [INFO|DP=0|PP=6|TP=7|ip-26-0-172-142]: [After model building] Memory usage: 44.04MiB. Peak allocated: 46.07MiB Peak reserved: 52.00MiB
[default3]:07/06/2024 09:35:24 [INFO|DP=0|PP=2|TP=3|ip-26-0-163-147]: [After model building] Memory usage: 33.03MiB. Peak allocated: 35.06MiB Peak reserved: 50.00MiB
[default7]:07/06/2024 09:35:24 [INFO|DP=0|PP=4|TP=7|ip-26-0-165-213]: Local number of parameters: 15.7M (30.02MiB)
[default5]:07/06/2024 09:35:24 [INFO|DP=0|PP=1|TP=5|ip-26-0-161-138]: No checkpoint path provided.
[default7]:07/06/2024 09:35:24 [INFO|DP=0|PP=6|TP=7|ip-26-0-172-142]: No checkpoint path provided.
[default3]:07/06/2024 09:35:24 [INFO|DP=0|PP=2|TP=3|ip-26-0-163-147]: No checkpoint path provided.
[default2]:07/06/2024 09:35:24 [INFO|DP=0|PP=4|TP=2|ip-26-0-165-213]: Local number of parameters: 15.7M (30.02MiB)
[default2]:07/06/2024 09:35:24 [INFO|DP=0|PP=4|TP=2|ip-26-0-165-213]: [After model building] Memory usage: 33.03MiB. Peak allocated: 35.06MiB Peak reserved: 50.00MiB
[default2]:07/06/2024 09:35:24 [INFO|DP=0|PP=1|TP=2|ip-26-0-161-138]: Local number of parameters: 15.7M (30.02MiB)
[default3]:07/06/2024 09:35:24 [INFO|DP=0|PP=6|TP=3|ip-26-0-172-142]: Local number of parameters: 21M (40.03MiB)
[default5]:07/06/2024 09:35:24 [INFO|DP=0|PP=2|TP=5|ip-26-0-163-147]: Local number of parameters: 15.7M (30.02MiB)
[default4]:07/06/2024 09:35:24 [INFO|DP=0|PP=2|TP=4|ip-26-0-163-147]: Local number of parameters: 15.7M (30.02MiB)
[default7]:07/06/2024 09:35:24 [INFO|DP=0|PP=4|TP=7|ip-26-0-165-213]: [After model building] Memory usage: 33.03MiB. Peak allocated: 35.06MiB Peak reserved: 50.00MiB
[default2]:07/06/2024 09:35:24 [INFO|DP=0|PP=1|TP=2|ip-26-0-161-138]: [After model building] Memory usage: 33.03MiB. Peak allocated: 35.06MiB Peak reserved: 50.00MiB
[default2]:07/06/2024 09:35:24 [INFO|DP=0|PP=1|TP=2|ip-26-0-161-138]: No checkpoint path provided.
[default3]:07/06/2024 09:35:24 [INFO|DP=0|PP=6|TP=3|ip-26-0-172-142]: [After model building] Memory usage: 44.04MiB. Peak allocated: 46.07MiB Peak reserved: 52.00MiB
[default4]:07/06/2024 09:35:24 [INFO|DP=0|PP=2|TP=4|ip-26-0-163-147]: [After model building] Memory usage: 33.03MiB. Peak allocated: 35.06MiB Peak reserved: 50.00MiB
[default4]:07/06/2024 09:35:24 [INFO|DP=0|PP=4|TP=4|ip-26-0-165-213]: Local number of parameters: 15.7M (30.02MiB)
[default1]:07/06/2024 09:35:24 [INFO|DP=0|PP=1|TP=1|ip-26-0-161-138]: Local number of parameters: 15.7M (30.02MiB)
[default3]:07/06/2024 09:35:24 [INFO|DP=0|PP=6|TP=3|ip-26-0-172-142]: No checkpoint path provided.
[default1]:07/06/2024 09:35:24 [INFO|DP=0|PP=0|TP=1|ip-26-0-160-103]: Local number of parameters: 33.9M (64.57MiB)
[default1]:07/06/2024 09:35:24 [INFO|DP=0|PP=0|TP=1|ip-26-0-160-103]: [After model building] Memory usage: 68.59MiB. Peak allocated: 70.62MiB Peak reserved: 78.00MiB
[default5]:07/06/2024 09:35:24 [INFO|DP=0|PP=2|TP=5|ip-26-0-163-147]: [After model building] Memory usage: 33.03MiB. Peak allocated: 35.06MiB Peak reserved: 50.00MiB
[default7]:07/06/2024 09:35:24 [INFO|DP=0|PP=4|TP=7|ip-26-0-165-213]: No checkpoint path provided.
[default7]:07/06/2024 09:35:24 [INFO|DP=0|PP=1|TP=7|ip-26-0-161-138]: Local number of parameters: 15.7M (30.02MiB)
[default7]:07/06/2024 09:35:24 [INFO|DP=0|PP=1|TP=7|ip-26-0-161-138]: [After model building] Memory usage: 33.03MiB. Peak allocated: 35.06MiB Peak reserved: 50.00MiB
[default2]:07/06/2024 09:35:24 [INFO|DP=0|PP=6|TP=2|ip-26-0-172-142]: Local number of parameters: 21M (40.03MiB)
[default1]:07/06/2024 09:35:24 [INFO|DP=0|PP=0|TP=1|ip-26-0-160-103]: No checkpoint path provided.
[default5]:07/06/2024 09:35:24 [INFO|DP=0|PP=2|TP=5|ip-26-0-163-147]: No checkpoint path provided.
[default4]:07/06/2024 09:35:24 [INFO|DP=0|PP=4|TP=4|ip-26-0-165-213]: [After model building] Memory usage: 33.03MiB. Peak allocated: 35.06MiB Peak reserved: 50.00MiB
[default7]:07/06/2024 09:35:24 [INFO|DP=0|PP=1|TP=7|ip-26-0-161-138]: No checkpoint path provided.
[default2]:07/06/2024 09:35:24 [INFO|DP=0|PP=6|TP=2|ip-26-0-172-142]: [After model building] Memory usage: 44.04MiB. Peak allocated: 46.07MiB Peak reserved: 52.00MiB
[default2]:07/06/2024 09:35:24 [INFO|DP=0|PP=6|TP=2|ip-26-0-172-142]: No checkpoint path provided.
[default2]:07/06/2024 09:35:24 [INFO|DP=0|PP=0|TP=2|ip-26-0-160-103]: Local number of parameters: 33.9M (64.57MiB)
[default4]:07/06/2024 09:35:24 [INFO|DP=0|PP=2|TP=4|ip-26-0-163-147]: No checkpoint path provided.
[default4]:07/06/2024 09:35:24 [INFO|DP=0|PP=4|TP=4|ip-26-0-165-213]: No checkpoint path provided.
[default2]:07/06/2024 09:35:24 [INFO|DP=0|PP=4|TP=2|ip-26-0-165-213]: No checkpoint path provided.
[default1]:07/06/2024 09:35:24 [INFO|DP=0|PP=1|TP=1|ip-26-0-161-138]: [After model building] Memory usage: 33.03MiB. Peak allocated: 35.06MiB Peak reserved: 50.00MiB
[default1]:07/06/2024 09:35:24 [INFO|DP=0|PP=1|TP=1|ip-26-0-161-138]: No checkpoint path provided.
[default2]:07/06/2024 09:35:24 [INFO|DP=0|PP=0|TP=2|ip-26-0-160-103]: [After model building] Memory usage: 68.59MiB. Peak allocated: 70.62MiB Peak reserved: 78.00MiB
[default7]:07/06/2024 09:35:24 [INFO|DP=0|PP=2|TP=7|ip-26-0-163-147]: Local number of parameters: 15.7M (30.02MiB)
[default7]:07/06/2024 09:35:24 [INFO|DP=0|PP=2|TP=7|ip-26-0-163-147]: [After model building] Memory usage: 33.03MiB. Peak allocated: 35.06MiB Peak reserved: 50.00MiB
[default7]:07/06/2024 09:35:24 [INFO|DP=0|PP=5|TP=7|ip-26-0-166-15]: Local number of parameters: 15.7M (30.02MiB)
[default7]:07/06/2024 09:35:24 [INFO|DP=0|PP=5|TP=7|ip-26-0-166-15]: [After model building] Memory usage: 33.03MiB. Peak allocated: 35.06MiB Peak reserved: 50.00MiB
[default7]:07/06/2024 09:35:24 [INFO|DP=0|PP=5|TP=7|ip-26-0-166-15]: No checkpoint path provided.
[default2]:07/06/2024 09:35:24 [INFO|DP=0|PP=0|TP=2|ip-26-0-160-103]: No checkpoint path provided.
[default7]:07/06/2024 09:35:24 [INFO|DP=0|PP=2|TP=7|ip-26-0-163-147]: No checkpoint path provided.
[default4]:07/06/2024 09:35:24 [INFO|DP=0|PP=5|TP=4|ip-26-0-166-15]: Local number of parameters: 15.7M (30.02MiB)
[default4]:07/06/2024 09:35:24 [INFO|DP=0|PP=5|TP=4|ip-26-0-166-15]: [After model building] Memory usage: 33.03MiB. Peak allocated: 35.06MiB Peak reserved: 50.00MiB
[default5]:07/06/2024 09:35:24 [INFO|DP=0|PP=0|TP=5|ip-26-0-160-103]: Local number of parameters: 33.9M (64.57MiB)
[default4]:07/06/2024 09:35:24 [INFO|DP=0|PP=5|TP=4|ip-26-0-166-15]: No checkpoint path provided.
[default5]:07/06/2024 09:35:24 [INFO|DP=0|PP=5|TP=5|ip-26-0-166-15]: Local number of parameters: 15.7M (30.02MiB)
[default5]:07/06/2024 09:35:24 [INFO|DP=0|PP=0|TP=5|ip-26-0-160-103]: [After model building] Memory usage: 68.59MiB. Peak allocated: 70.62MiB Peak reserved: 78.00MiB
[default0]:07/06/2024 09:35:24 [INFO|DP=0|PP=5|TP=0|ip-26-0-166-15]: Local number of parameters: 15.7M (30.02MiB)
[default5]:07/06/2024 09:35:24 [INFO|DP=0|PP=0|TP=5|ip-26-0-160-103]: No checkpoint path provided.
[default6]:07/06/2024 09:35:24 [INFO|DP=0|PP=5|TP=6|ip-26-0-166-15]: Local number of parameters: 15.7M (30.02MiB)
[default6]:07/06/2024 09:35:24 [INFO|DP=0|PP=5|TP=6|ip-26-0-166-15]: [After model building] Memory usage: 33.03MiB. Peak allocated: 35.06MiB Peak reserved: 50.00MiB
[default0]:07/06/2024 09:35:24 [INFO|DP=0|PP=0|TP=0|ip-26-0-160-103]: Total number of parameters: 1.21G (2314.22MiB)
[default0]:07/06/2024 09:35:24 [INFO|DP=0|PP=0|TP=0|ip-26-0-160-103]: Local number of parameters: 33.9M (64.57MiB)
[default0]:07/06/2024 09:35:24 [INFO|DP=0|PP=0|TP=0|ip-26-0-160-103]: [After model building] Memory usage: 68.59MiB. Peak allocated: 70.62MiB Peak reserved: 78.00MiB
[default0]:07/06/2024 09:35:24 [INFO|DP=0|PP=0|TP=0|ip-26-0-160-103]: No checkpoint path provided.
[default0]:07/06/2024 09:35:24 [INFO|DP=0|PP=0|TP=0|ip-26-0-160-103]: Parametrizing model parameters using StandardParametrizator
[default6]:07/06/2024 09:35:24 [INFO|DP=0|PP=5|TP=6|ip-26-0-166-15]: No checkpoint path provided.
[default3]:07/06/2024 09:35:24 [INFO|DP=0|PP=0|TP=3|ip-26-0-160-103]: Local number of parameters: 33.9M (64.57MiB)
[default0]:07/06/2024 09:35:24 [INFO|DP=0|PP=5|TP=0|ip-26-0-166-15]: [After model building] Memory usage: 33.03MiB. Peak allocated: 35.06MiB Peak reserved: 50.00MiB
[default0]:07/06/2024 09:35:24 [INFO|DP=0|PP=5|TP=0|ip-26-0-166-15]: No checkpoint path provided.
[default3]:07/06/2024 09:35:24 [INFO|DP=0|PP=0|TP=3|ip-26-0-160-103]: [After model building] Memory usage: 68.59MiB. Peak allocated: 70.62MiB Peak reserved: 78.00MiB
[default3]:07/06/2024 09:35:24 [INFO|DP=0|PP=0|TP=3|ip-26-0-160-103]: No checkpoint path provided.
[default1]:07/06/2024 09:35:24 [INFO|DP=0|PP=5|TP=1|ip-26-0-166-15]: Local number of parameters: 15.7M (30.02MiB)
[default6]:07/06/2024 09:35:24 [INFO|DP=0|PP=0|TP=6|ip-26-0-160-103]: Local number of parameters: 33.9M (64.57MiB)
[default6]:07/06/2024 09:35:24 [INFO|DP=0|PP=0|TP=6|ip-26-0-160-103]: [After model building] Memory usage: 68.59MiB. Peak allocated: 70.62MiB Peak reserved: 78.00MiB
[default5]:07/06/2024 09:35:24 [INFO|DP=0|PP=5|TP=5|ip-26-0-166-15]: [After model building] Memory usage: 33.03MiB. Peak allocated: 35.06MiB Peak reserved: 50.00MiB
[default5]:07/06/2024 09:35:24 [INFO|DP=0|PP=5|TP=5|ip-26-0-166-15]: No checkpoint path provided.
[default1]:07/06/2024 09:35:24 [INFO|DP=0|PP=5|TP=1|ip-26-0-166-15]: [After model building] Memory usage: 33.03MiB. Peak allocated: 35.06MiB Peak reserved: 50.00MiB
[default6]:07/06/2024 09:35:24 [INFO|DP=0|PP=0|TP=6|ip-26-0-160-103]: No checkpoint path provided.
[default1]:07/06/2024 09:35:24 [INFO|DP=0|PP=5|TP=1|ip-26-0-166-15]: No checkpoint path provided.
[default7]:07/06/2024 09:35:24 [INFO|DP=0|PP=0|TP=7|ip-26-0-160-103]: Local number of parameters: 33.9M (64.57MiB)
[default3]:07/06/2024 09:35:24 [INFO|DP=0|PP=5|TP=3|ip-26-0-166-15]: Local number of parameters: 15.7M (30.02MiB)
[default3]:07/06/2024 09:35:24 [INFO|DP=0|PP=5|TP=3|ip-26-0-166-15]: [After model building] Memory usage: 33.03MiB. Peak allocated: 35.06MiB Peak reserved: 50.00MiB
[default7]:07/06/2024 09:35:24 [INFO|DP=0|PP=0|TP=7|ip-26-0-160-103]: [After model building] Memory usage: 68.59MiB. Peak allocated: 70.62MiB Peak reserved: 78.00MiB
[default7]:07/06/2024 09:35:24 [INFO|DP=0|PP=0|TP=7|ip-26-0-160-103]: No checkpoint path provided.
[default3]:07/06/2024 09:35:24 [INFO|DP=0|PP=5|TP=3|ip-26-0-166-15]: No checkpoint path provided.
[default4]:07/06/2024 09:35:24 [INFO|DP=0|PP=0|TP=4|ip-26-0-160-103]: Local number of parameters: 33.9M (64.57MiB)
[default2]:07/06/2024 09:35:24 [INFO|DP=0|PP=5|TP=2|ip-26-0-166-15]: Local number of parameters: 15.7M (30.02MiB)
[default2]:07/06/2024 09:35:24 [INFO|DP=0|PP=5|TP=2|ip-26-0-166-15]: [After model building] Memory usage: 33.03MiB. Peak allocated: 35.06MiB Peak reserved: 50.00MiB
[default2]:07/06/2024 09:35:24 [INFO|DP=0|PP=5|TP=2|ip-26-0-166-15]: No checkpoint path provided.
[default4]:07/06/2024 09:35:24 [INFO|DP=0|PP=0|TP=4|ip-26-0-160-103]: [After model building] Memory usage: 68.59MiB. Peak allocated: 70.62MiB Peak reserved: 78.00MiB
[default4]:07/06/2024 09:35:24 [INFO|DP=0|PP=0|TP=4|ip-26-0-160-103]: No checkpoint path provided.
[default0]:07/06/2024 09:35:26 [INFO|DP=0|PP=0|TP=0|ip-26-0-160-103]: [Optimizer Building] Using LearningRateForSP as learning rate
[default0]:07/06/2024 09:35:26 [INFO|DP=0|PP=0|TP=0|ip-26-0-160-103]: [ZeRO sharding] Size of optimizer params per rank:
[default0]:07/06/2024 09:35:26 [INFO|DP=0|PP=0|TP=0|ip-26-0-160-103]: [ZeRO sharding] DP Rank 0 has 33.9M out of 33.9M (100.00%) params' optimizer states
[default0]:07/06/2024 09:35:27 [INFO|DP=0|PP=0|TP=0|ip-26-0-160-103]: [Training Plan] Stage Training Stage has 19 remaining training steps and has consumed 0 samples
[default0]:07/06/2024 09:35:27 [INFO|DP=0|PP=0|TP=0|ip-26-0-160-103]: Using `datasets` library
[default0]:07/06/2024 09:35:27 [INFO|DP=0|PP=0|TP=0|ip-26-0-160-103]: Loading tokenizer from openai-community/gpt2 and transformers/hf_hub versions ('4.41.2', '0.23.4')
[default0]:07/06/2024 09:35:27 [WARNING|DP=0|PP=0|TP=0|ip-26-0-160-103]: Repo card metadata block was not found. Setting CardData to empty.
[default0]:Repo card metadata block was not found. Setting CardData to empty.
[default0]:07/06/2024 09:35:28 [INFO|DP=0|PP=0|TP=0|ip-26-0-160-103]: [Training Plan] There are 1 training stages 
[default0]:07/06/2024 09:35:28 [INFO|DP=0|PP=0|TP=0|ip-26-0-160-103]: [Stage Training Stage] start from step 1 
[default0]:07/06/2024 09:35:28 [INFO|DP=0|PP=0|TP=0|ip-26-0-160-103]: 
[default0]:07/06/2024 09:35:28 [INFO|DP=0|PP=0|TP=0|ip-26-0-160-103]: [Start training] datetime: 2024-07-06 09:35:28.190844 | mbs: 8 | grad_accum: 128 | global_batch_size: 1024 | sequence_length: 4096 | train_steps: 20 | start_iteration_step: 0 | consumed_train_samples: 0
[default6]:07/06/2024 09:35:28 [WARNING|DP=0|PP=7|TP=6|ip-26-0-172-147]: Repo card metadata block was not found. Setting CardData to empty.
[default1]:Repo card metadata block was not found. Setting CardData to empty.
[default0]:07/06/2024 09:35:28 [WARNING|DP=0|PP=7|TP=0|ip-26-0-172-147]: Repo card metadata block was not found. Setting CardData to empty.
[default1]:07/06/2024 09:35:28 [WARNING|DP=0|PP=7|TP=1|ip-26-0-172-147]: Repo card metadata block was not found. Setting CardData to empty.
[default2]:Repo card metadata block was not found. Setting CardData to empty.
[default2]:07/06/2024 09:35:28 [WARNING|DP=0|PP=7|TP=2|ip-26-0-172-147]: Repo card metadata block was not found. Setting CardData to empty.
[default0]:07/06/2024 09:35:28 [WARNING|DP=0|PP=2|TP=0|ip-26-0-163-147]: Repo card metadata block was not found. Setting CardData to empty.
[default0]:Repo card metadata block was not found. Setting CardData to empty.
[default2]:Repo card metadata block was not found. Setting CardData to empty.
[default7]:07/06/2024 09:35:28 [WARNING|DP=0|PP=3|TP=7|ip-26-0-163-58]: Repo card metadata block was not found. Setting CardData to empty.
[default5]:Repo card metadata block was not found. Setting CardData to empty.
[default0]:07/06/2024 09:35:28 [WARNING|DP=0|PP=6|TP=0|ip-26-0-172-142]: Repo card metadata block was not found. Setting CardData to empty.
[default2]:07/06/2024 09:35:28 [WARNING|DP=0|PP=3|TP=2|ip-26-0-163-58]: Repo card metadata block was not found. Setting CardData to empty.
[default6]:Repo card metadata block was not found. Setting CardData to empty.
[default7]:Repo card metadata block was not found. Setting CardData to empty.
[default7]:Repo card metadata block was not found. Setting CardData to empty.
[default0]:07/06/2024 09:35:28 [WARNING|DP=0|PP=1|TP=0|ip-26-0-161-138]: Repo card metadata block was not found. Setting CardData to empty.
[default6]:07/06/2024 09:35:28 [WARNING|DP=0|PP=1|TP=6|ip-26-0-161-138]: Repo card metadata block was not found. Setting CardData to empty.
[default3]:07/06/2024 09:35:28 [WARNING|DP=0|PP=4|TP=3|ip-26-0-165-213]: Repo card metadata block was not found. Setting CardData to empty.
[default6]:07/06/2024 09:35:28 [WARNING|DP=0|PP=4|TP=6|ip-26-0-165-213]: Repo card metadata block was not found. Setting CardData to empty.
[default1]:Repo card metadata block was not found. Setting CardData to empty.
[default1]:07/06/2024 09:35:28 [WARNING|DP=0|PP=6|TP=1|ip-26-0-172-142]: Repo card metadata block was not found. Setting CardData to empty.
[default0]:Repo card metadata block was not found. Setting CardData to empty.
[default5]:07/06/2024 09:35:28 [WARNING|DP=0|PP=6|TP=5|ip-26-0-172-142]: Repo card metadata block was not found. Setting CardData to empty.
[default1]:07/06/2024 09:35:28 [WARNING|DP=0|PP=2|TP=1|ip-26-0-163-147]: Repo card metadata block was not found. Setting CardData to empty.
[default6]:07/06/2024 09:35:28 [WARNING|DP=0|PP=2|TP=6|ip-26-0-163-147]: Repo card metadata block was not found. Setting CardData to empty.
[default5]:07/06/2024 09:35:28 [WARNING|DP=0|PP=4|TP=5|ip-26-0-165-213]: Repo card metadata block was not found. Setting CardData to empty.
[default4]:07/06/2024 09:35:28 [WARNING|DP=0|PP=2|TP=4|ip-26-0-163-147]: Repo card metadata block was not found. Setting CardData to empty.
[default1]:Repo card metadata block was not found. Setting CardData to empty.
[default3]:07/06/2024 09:35:28 [WARNING|DP=0|PP=2|TP=3|ip-26-0-163-147]: Repo card metadata block was not found. Setting CardData to empty.
[default3]:Repo card metadata block was not found. Setting CardData to empty.
[default2]:07/06/2024 09:35:28 [WARNING|DP=0|PP=4|TP=2|ip-26-0-165-213]: Repo card metadata block was not found. Setting CardData to empty.
[default0]:Repo card metadata block was not found. Setting CardData to empty.
[default5]:07/06/2024 09:35:28 [WARNING|DP=0|PP=1|TP=5|ip-26-0-161-138]: Repo card metadata block was not found. Setting CardData to empty.
[default0]:Repo card metadata block was not found. Setting CardData to empty.
[default1]:07/06/2024 09:35:28 [WARNING|DP=0|PP=1|TP=1|ip-26-0-161-138]: Repo card metadata block was not found. Setting CardData to empty.
[default4]:Repo card metadata block was not found. Setting CardData to empty.
[default7]:07/06/2024 09:35:28 [WARNING|DP=0|PP=1|TP=7|ip-26-0-161-138]: Repo card metadata block was not found. Setting CardData to empty.
[default5]:Repo card metadata block was not found. Setting CardData to empty.
[default3]:Repo card metadata block was not found. Setting CardData to empty.
[default1]:07/06/2024 09:35:28 [WARNING|DP=0|PP=0|TP=1|ip-26-0-160-103]: Repo card metadata block was not found. Setting CardData to empty.
[default1]:Repo card metadata block was not found. Setting CardData to empty.
[default2]:Repo card metadata block was not found. Setting CardData to empty.
[default2]:Repo card metadata block was not found. Setting CardData to empty.
[default2]:07/06/2024 09:35:28 [WARNING|DP=0|PP=0|TP=2|ip-26-0-160-103]: Repo card metadata block was not found. Setting CardData to empty.
[default6]:Repo card metadata block was not found. Setting CardData to empty.
[default7]:07/06/2024 09:35:28 [WARNING|DP=0|PP=5|TP=7|ip-26-0-166-15]: Repo card metadata block was not found. Setting CardData to empty.
[default6]:Repo card metadata block was not found. Setting CardData to empty.
[default6]:07/06/2024 09:35:28 [WARNING|DP=0|PP=5|TP=6|ip-26-0-166-15]: Repo card metadata block was not found. Setting CardData to empty.
[default5]:07/06/2024 09:35:28 [WARNING|DP=0|PP=5|TP=5|ip-26-0-166-15]: Repo card metadata block was not found. Setting CardData to empty.
[default6]:Repo card metadata block was not found. Setting CardData to empty.
[default5]:Repo card metadata block was not found. Setting CardData to empty.
[default0]:07/06/2024 09:35:28 [WARNING|DP=0|PP=5|TP=0|ip-26-0-166-15]: Repo card metadata block was not found. Setting CardData to empty.
[default4]:Repo card metadata block was not found. Setting CardData to empty.
[default7]:07/06/2024 09:35:28 [WARNING|DP=0|PP=0|TP=7|ip-26-0-160-103]: Repo card metadata block was not found. Setting CardData to empty.
[default7]:Repo card metadata block was not found. Setting CardData to empty.
[default4]:07/06/2024 09:35:28 [WARNING|DP=0|PP=5|TP=4|ip-26-0-166-15]: Repo card metadata block was not found. Setting CardData to empty.
[default1]:07/06/2024 09:35:28 [WARNING|DP=0|PP=5|TP=1|ip-26-0-166-15]: Repo card metadata block was not found. Setting CardData to empty.
[default1]:Repo card metadata block was not found. Setting CardData to empty.
[default4]:07/06/2024 09:35:28 [WARNING|DP=0|PP=0|TP=4|ip-26-0-160-103]: Repo card metadata block was not found. Setting CardData to empty.
[default5]:Repo card metadata block was not found. Setting CardData to empty.
[default2]:Repo card metadata block was not found. Setting CardData to empty.
[default2]:07/06/2024 09:35:28 [WARNING|DP=0|PP=5|TP=2|ip-26-0-166-15]: Repo card metadata block was not found. Setting CardData to empty.
[default4]:Repo card metadata block was not found. Setting CardData to empty.
[default1]:Repo card metadata block was not found. Setting CardData to empty.
[default7]:Repo card metadata block was not found. Setting CardData to empty.
[default0]:Repo card metadata block was not found. Setting CardData to empty.
[default6]:Repo card metadata block was not found. Setting CardData to empty.
[default4]:Repo card metadata block was not found. Setting CardData to empty.
[default3]:07/06/2024 09:35:28 [WARNING|DP=0|PP=7|TP=3|ip-26-0-172-147]: Repo card metadata block was not found. Setting CardData to empty.
[default7]:07/06/2024 09:35:28 [WARNING|DP=0|PP=7|TP=7|ip-26-0-172-147]: Repo card metadata block was not found. Setting CardData to empty.
[default4]:07/06/2024 09:35:28 [WARNING|DP=0|PP=3|TP=4|ip-26-0-163-58]: Repo card metadata block was not found. Setting CardData to empty.
[default7]:Repo card metadata block was not found. Setting CardData to empty.
[default0]:07/06/2024 09:35:28 [WARNING|DP=0|PP=3|TP=0|ip-26-0-163-58]: Repo card metadata block was not found. Setting CardData to empty.
[default5]:07/06/2024 09:35:28 [WARNING|DP=0|PP=3|TP=5|ip-26-0-163-58]: Repo card metadata block was not found. Setting CardData to empty.
[default5]:07/06/2024 09:35:28 [WARNING|DP=0|PP=7|TP=5|ip-26-0-172-147]: Repo card metadata block was not found. Setting CardData to empty.
[default2]:Repo card metadata block was not found. Setting CardData to empty.
[default6]:Repo card metadata block was not found. Setting CardData to empty.
[default5]:Repo card metadata block was not found. Setting CardData to empty.
[default6]:07/06/2024 09:35:28 [WARNING|DP=0|PP=3|TP=6|ip-26-0-163-58]: Repo card metadata block was not found. Setting CardData to empty.
[default0]:Repo card metadata block was not found. Setting CardData to empty.
[default4]:Repo card metadata block was not found. Setting CardData to empty.
[default4]:07/06/2024 09:35:28 [WARNING|DP=0|PP=7|TP=4|ip-26-0-172-147]: Repo card metadata block was not found. Setting CardData to empty.
[default5]:Repo card metadata block was not found. Setting CardData to empty.
[default3]:Repo card metadata block was not found. Setting CardData to empty.
[default3]:Repo card metadata block was not found. Setting CardData to empty.
[default4]:07/06/2024 09:35:28 [WARNING|DP=0|PP=1|TP=4|ip-26-0-161-138]: Repo card metadata block was not found. Setting CardData to empty.
[default1]:07/06/2024 09:35:28 [WARNING|DP=0|PP=4|TP=1|ip-26-0-165-213]: Repo card metadata block was not found. Setting CardData to empty.
[default2]:Repo card metadata block was not found. Setting CardData to empty.
[default4]:07/06/2024 09:35:28 [WARNING|DP=0|PP=6|TP=4|ip-26-0-172-142]: Repo card metadata block was not found. Setting CardData to empty.
[default2]:07/06/2024 09:35:28 [WARNING|DP=0|PP=2|TP=2|ip-26-0-163-147]: Repo card metadata block was not found. Setting CardData to empty.
[default2]:07/06/2024 09:35:28 [WARNING|DP=0|PP=1|TP=2|ip-26-0-161-138]: Repo card metadata block was not found. Setting CardData to empty.
[default7]:07/06/2024 09:35:28 [WARNING|DP=0|PP=2|TP=7|ip-26-0-163-147]: Repo card metadata block was not found. Setting CardData to empty.
[default1]:Repo card metadata block was not found. Setting CardData to empty.
[default3]:07/06/2024 09:35:28 [WARNING|DP=0|PP=6|TP=3|ip-26-0-172-142]: Repo card metadata block was not found. Setting CardData to empty.
[default4]:07/06/2024 09:35:28 [WARNING|DP=0|PP=4|TP=4|ip-26-0-165-213]: Repo card metadata block was not found. Setting CardData to empty.
[default3]:07/06/2024 09:35:28 [WARNING|DP=0|PP=1|TP=3|ip-26-0-161-138]: Repo card metadata block was not found. Setting CardData to empty.
[default7]:07/06/2024 09:35:28 [WARNING|DP=0|PP=6|TP=7|ip-26-0-172-142]: Repo card metadata block was not found. Setting CardData to empty.
[default7]:07/06/2024 09:35:28 [WARNING|DP=0|PP=4|TP=7|ip-26-0-165-213]: Repo card metadata block was not found. Setting CardData to empty.
[default4]:Repo card metadata block was not found. Setting CardData to empty.
[default4]:Repo card metadata block was not found. Setting CardData to empty.
[default3]:Repo card metadata block was not found. Setting CardData to empty.
[default7]:Repo card metadata block was not found. Setting CardData to empty.
[default5]:07/06/2024 09:35:28 [WARNING|DP=0|PP=0|TP=5|ip-26-0-160-103]: Repo card metadata block was not found. Setting CardData to empty.
[default4]:Repo card metadata block was not found. Setting CardData to empty.
[default7]:Repo card metadata block was not found. Setting CardData to empty.
[default5]:Repo card metadata block was not found. Setting CardData to empty.
[default6]:Repo card metadata block was not found. Setting CardData to empty.
[default6]:07/06/2024 09:35:28 [WARNING|DP=0|PP=0|TP=6|ip-26-0-160-103]: Repo card metadata block was not found. Setting CardData to empty.
[default7]:Repo card metadata block was not found. Setting CardData to empty.
[default3]:07/06/2024 09:35:28 [WARNING|DP=0|PP=0|TP=3|ip-26-0-160-103]: Repo card metadata block was not found. Setting CardData to empty.
[default3]:Repo card metadata block was not found. Setting CardData to empty.
[default3]:07/06/2024 09:35:28 [WARNING|DP=0|PP=5|TP=3|ip-26-0-166-15]: Repo card metadata block was not found. Setting CardData to empty.
[default3]:Repo card metadata block was not found. Setting CardData to empty.
[default3]:07/06/2024 09:35:28 [WARNING|DP=0|PP=3|TP=3|ip-26-0-163-58]: Repo card metadata block was not found. Setting CardData to empty.
[default1]:07/06/2024 09:35:28 [WARNING|DP=0|PP=3|TP=1|ip-26-0-163-58]: Repo card metadata block was not found. Setting CardData to empty.
[default2]:Repo card metadata block was not found. Setting CardData to empty.
[default1]:Repo card metadata block was not found. Setting CardData to empty.
[default3]:Repo card metadata block was not found. Setting CardData to empty.
[default6]:07/06/2024 09:35:28 [WARNING|DP=0|PP=6|TP=6|ip-26-0-172-142]: Repo card metadata block was not found. Setting CardData to empty.
[default2]:07/06/2024 09:35:28 [WARNING|DP=0|PP=6|TP=2|ip-26-0-172-142]: Repo card metadata block was not found. Setting CardData to empty.
[default6]:Repo card metadata block was not found. Setting CardData to empty.
[default0]:Repo card metadata block was not found. Setting CardData to empty.
[default0]:07/06/2024 09:35:28 [WARNING|DP=0|PP=4|TP=0|ip-26-0-165-213]: Repo card metadata block was not found. Setting CardData to empty.
[default5]:Repo card metadata block was not found. Setting CardData to empty.
[default5]:07/06/2024 09:35:28 [WARNING|DP=0|PP=2|TP=5|ip-26-0-163-147]: Repo card metadata block was not found. Setting CardData to empty.
[default0]:07/06/2024 09:35:34 [INFO|DP=0|PP=0|TP=0|ip-26-0-160-103]: Resuming training from stage Training Stage, it has trained for 0 samples and has 19 remaining train steps
[default0]:07/06/2024 09:35:34 [INFO|DP=0|PP=0|TP=0|ip-26-0-160-103]:  Memory usage: 328.58MiB. Peak allocated 328.59MiB. Peak reserved: 338.00MiB
[default5]:Traceback (most recent call last):
[default5]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/run_train.py", line 237, in <module>
[default5]:    trainer.train(dataloader)
[default5]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/trainer.py", line 430, in train
[default5]:    outputs, loss_avg = self.training_step(dataloader=self.current_dataloader)
[default5]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/trainer.py", line 459, in training_step
[default5]:    outputs = self.pipeline_engine.train_batch_iter(
[default5]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/engine.py", line 187, in train_batch_iter
[default5]:    output = self.forward(context=context, state=state, micro_batch=micro_batch, model=model)
[default5]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/engine.py", line 44, in forward
[default5]:    output = model(**micro_batch)
[default5]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1511, in _wrapped_call_impl
[default5]:    return self._call_impl(*args, **kwargs)
[default5]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1520, in _call_impl
[default5]:    return forward_call(*args, **kwargs)
[default5]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 890, in forward
[default5]:    sharded_logits = self.model(
[default5]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1511, in _wrapped_call_impl
[default5]:    return self._call_impl(*args, **kwargs)
[default5]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1520, in _call_impl
[default5]:    return forward_call(*args, **kwargs)
[default5]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 764, in forward
[default5]:    return self.forward_with_hidden_states(input_ids=input_ids, input_mask=input_mask)[0]
[default5]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 780, in forward_with_hidden_states
[default3]:Traceback (most recent call last):
[default3]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/run_train.py", line 237, in <module>
[default5]:    hidden_encoder_states = encoder_block(**hidden_encoder_states)
[default3]:    trainer.train(dataloader)
[default6]:Traceback (most recent call last):
[default6]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/run_train.py", line 237, in <module>
[default5]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1511, in _wrapped_call_impl
[default6]:    trainer.train(dataloader)
[default3]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/trainer.py", line 430, in train
[default5]:    return self._call_impl(*args, **kwargs)
[default6]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/trainer.py", line 430, in train
[default5]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1520, in _call_impl
[default3]:    outputs, loss_avg = self.training_step(dataloader=self.current_dataloader)
[default6]:    outputs, loss_avg = self.training_step(dataloader=self.current_dataloader)
[default5]:    return forward_call(*args, **kwargs)
[default6]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/trainer.py", line 459, in training_step
[default5]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/block.py", line 151, in forward
[default3]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/trainer.py", line 459, in training_step
[default6]:    outputs = self.pipeline_engine.train_batch_iter(
[default3]:    outputs = self.pipeline_engine.train_batch_iter(
[default5]:    output = self.pp_block(**new_kwargs)
[default5]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1511, in _wrapped_call_impl
[default3]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/engine.py", line 187, in train_batch_iter
[default3]:    output = self.forward(context=context, state=state, micro_batch=micro_batch, model=model)
[default5]:    return self._call_impl(*args, **kwargs)
[default3]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/engine.py", line 44, in forward
[default3]:    output = model(**micro_batch)
[default5]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1520, in _call_impl
[default6]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/engine.py", line 187, in train_batch_iter
[default6]:    output = self.forward(context=context, state=state, micro_batch=micro_batch, model=model)
[default5]:    return forward_call(*args, **kwargs)
[default6]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/engine.py", line 44, in forward
[default6]:    output = model(**micro_batch)
[default5]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 630, in forward
[default3]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1511, in _wrapped_call_impl
[default6]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1511, in _wrapped_call_impl
[default4]:Traceback (most recent call last):
[default5]:    output = self.attn(hidden_states=hidden_states, sequence_mask=sequence_mask)
[default3]:    return self._call_impl(*args, **kwargs)
[default6]:    return self._call_impl(*args, **kwargs)
[default3]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1520, in _call_impl
[default4]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/run_train.py", line 237, in <module>
[default4]:    trainer.train(dataloader)
[default4]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/trainer.py", line 430, in train
[default5]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1511, in _wrapped_call_impl
[default3]:    return forward_call(*args, **kwargs)
[default5]:    return self._call_impl(*args, **kwargs)
[default6]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1520, in _call_impl
[default6]:    return forward_call(*args, **kwargs)
[default5]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1520, in _call_impl
[default3]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 890, in forward
[default3]:    sharded_logits = self.model(
[default5]:    return forward_call(*args, **kwargs)
[default6]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 890, in forward
[default6]:    sharded_logits = self.model(
[default5]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 562, in forward
[default4]:    outputs, loss_avg = self.training_step(dataloader=self.current_dataloader)
[default6]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1511, in _wrapped_call_impl
[default5]:    key_value_states = torch.cat([key_states.unsqueeze(0), value_states.unsqueeze(0)], dim=0)
[default4]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/trainer.py", line 459, in training_step
[default4]:    outputs = self.pipeline_engine.train_batch_iter(
[default4]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/engine.py", line 187, in train_batch_iter
[default3]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1511, in _wrapped_call_impl
[default4]:    output = self.forward(context=context, state=state, micro_batch=micro_batch, model=model)
[default4]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/engine.py", line 44, in forward
[default4]:    output = model(**micro_batch)
[default6]:    return self._call_impl(*args, **kwargs)
[default5]:torch.cuda.OutOfMemoryError: CUDA out of memory. Tried to allocate 32.00 MiB. GPU 5 has a total capacity of 79.33 GiB of which 17.94 MiB is free. Including non-PyTorch memory, this process has 79.30 GiB memory in use. Of the allocated memory 69.78 GiB is allocated by PyTorch, and 12.14 MiB is reserved by PyTorch but unallocated. If reserved but unallocated memory is large try setting PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True to avoid fragmentation.  See documentation for Memory Management  (https://pytorch.org/docs/stable/notes/cuda.html#environment-variables)
[default2]:Traceback (most recent call last):
[default2]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/run_train.py", line 237, in <module>
[default6]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1520, in _call_impl
[default6]:    return forward_call(*args, **kwargs)
[default4]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1511, in _wrapped_call_impl
[default4]:    return self._call_impl(*args, **kwargs)
[default3]:    return self._call_impl(*args, **kwargs)
[default6]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 764, in forward
[default4]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1520, in _call_impl
[default3]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1520, in _call_impl
[default3]:    return forward_call(*args, **kwargs)
[default6]:    return self.forward_with_hidden_states(input_ids=input_ids, input_mask=input_mask)[0]
[default3]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 764, in forward
[default3]:    return self.forward_with_hidden_states(input_ids=input_ids, input_mask=input_mask)[0]
[default2]:    trainer.train(dataloader)
[default2]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/trainer.py", line 430, in train
[default4]:    return forward_call(*args, **kwargs)
[default6]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 780, in forward_with_hidden_states
[default2]:    outputs, loss_avg = self.training_step(dataloader=self.current_dataloader)
[default2]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/trainer.py", line 459, in training_step
[default2]:    outputs = self.pipeline_engine.train_batch_iter(
[default6]:    hidden_encoder_states = encoder_block(**hidden_encoder_states)
[default6]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1511, in _wrapped_call_impl
[default2]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/engine.py", line 187, in train_batch_iter
[default2]:    output = self.forward(context=context, state=state, micro_batch=micro_batch, model=model)
[default3]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 780, in forward_with_hidden_states
[default3]:    hidden_encoder_states = encoder_block(**hidden_encoder_states)
[default6]:    return self._call_impl(*args, **kwargs)
[default4]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 890, in forward
[default4]:    sharded_logits = self.model(
[default6]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1520, in _call_impl
[default6]:    return forward_call(*args, **kwargs)
[default3]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1511, in _wrapped_call_impl
[default4]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1511, in _wrapped_call_impl
[default6]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/block.py", line 151, in forward
[default3]:    return self._call_impl(*args, **kwargs)
[default3]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1520, in _call_impl
[default4]:    return self._call_impl(*args, **kwargs)
[default2]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/engine.py", line 44, in forward
[default2]:    output = model(**micro_batch)
[default4]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1520, in _call_impl
[default4]:    return forward_call(*args, **kwargs)
[default6]:    output = self.pp_block(**new_kwargs)
[default3]:    return forward_call(*args, **kwargs)
[default3]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/block.py", line 151, in forward
[default4]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 764, in forward
[default4]:    return self.forward_with_hidden_states(input_ids=input_ids, input_mask=input_mask)[0]
[default2]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1511, in _wrapped_call_impl
[default4]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 780, in forward_with_hidden_states
[default3]:    output = self.pp_block(**new_kwargs)
[default2]:    return self._call_impl(*args, **kwargs)
[default2]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1520, in _call_impl
[default6]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1511, in _wrapped_call_impl
[default6]:    return self._call_impl(*args, **kwargs)
[default2]:    return forward_call(*args, **kwargs)
[default3]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1511, in _wrapped_call_impl
[default3]:    return self._call_impl(*args, **kwargs)
[default4]:    hidden_encoder_states = encoder_block(**hidden_encoder_states)
[default4]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1511, in _wrapped_call_impl
[default4]:    return self._call_impl(*args, **kwargs)
[default2]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 890, in forward
[default6]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1520, in _call_impl
[default4]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1520, in _call_impl
[default2]:    sharded_logits = self.model(
[default3]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1520, in _call_impl
[default3]:    return forward_call(*args, **kwargs)
[default2]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1511, in _wrapped_call_impl
[default6]:    return forward_call(*args, **kwargs)
[default6]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 630, in forward
[default6]:    output = self.attn(hidden_states=hidden_states, sequence_mask=sequence_mask)
[default3]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 636, in forward
[default6]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1511, in _wrapped_call_impl
[default3]:    hidden_states = self.mlp(hidden_states=hidden_states)["hidden_states"]
[default6]:    return self._call_impl(*args, **kwargs)
[default2]:    return self._call_impl(*args, **kwargs)
[default2]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1520, in _call_impl
[default3]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1511, in _wrapped_call_impl
[default6]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1520, in _call_impl
[default3]:    return self._call_impl(*args, **kwargs)
[default6]:    return forward_call(*args, **kwargs)
[default2]:    return forward_call(*args, **kwargs)
[default2]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 764, in forward
[default6]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 562, in forward
[default6]:    key_value_states = torch.cat([key_states.unsqueeze(0), value_states.unsqueeze(0)], dim=0)
[default3]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1520, in _call_impl
[default6]:torch.cuda.OutOfMemoryError: CUDA out of memory. Tried to allocate 32.00 MiB. GPU 6 has a total capacity of 79.33 GiB of which 17.94 MiB is free. Including non-PyTorch memory, this process has 79.30 GiB memory in use. Of the allocated memory 69.78 GiB is allocated by PyTorch, and 12.14 MiB is reserved by PyTorch but unallocated. If reserved but unallocated memory is large try setting PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True to avoid fragmentation.  See documentation for Memory Management  (https://pytorch.org/docs/stable/notes/cuda.html#environment-variables)
[default3]:    return forward_call(*args, **kwargs)
[default3]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 171, in forward
[default3]:    hidden_states = self.down_proj(self.split_silu_mul(merged_states))
[default3]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1511, in _wrapped_call_impl
[default2]:    return self.forward_with_hidden_states(input_ids=input_ids, input_mask=input_mask)[0]
[default2]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 780, in forward_with_hidden_states
[default2]:    hidden_encoder_states = encoder_block(**hidden_encoder_states)
[default2]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1511, in _wrapped_call_impl
[default2]:    return self._call_impl(*args, **kwargs)
[default2]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1520, in _call_impl
[default3]:    return self._call_impl(*args, **kwargs)
[default3]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1520, in _call_impl
[default3]:    return forward_call(*args, **kwargs)
[default3]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/tensor_parallel/nn.py", line 159, in forward
[default2]:    return forward_call(*args, **kwargs)
[default2]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/block.py", line 151, in forward
[default2]:    output = self.pp_block(**new_kwargs)
[default2]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1511, in _wrapped_call_impl
[default2]:    return self._call_impl(*args, **kwargs)
[default2]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1520, in _call_impl
[default2]:    return forward_call(*args, **kwargs)
[default3]:    return row_linear(
[default3]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/tensor_parallel/functional.py", line 474, in row_linear
[default3]:    out = F.linear(input, weight, bias)
[default2]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 630, in forward
[default2]:    output = self.attn(hidden_states=hidden_states, sequence_mask=sequence_mask)
[default3]:torch.cuda.OutOfMemoryError: CUDA out of memory. Tried to allocate 128.00 MiB. GPU 3 has a total capacity of 79.33 GiB of which 97.94 MiB is free. Including non-PyTorch memory, this process has 79.22 GiB memory in use. Of the allocated memory 70.07 GiB is allocated by PyTorch, and 13.62 MiB is reserved by PyTorch but unallocated. If reserved but unallocated memory is large try setting PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True to avoid fragmentation.  See documentation for Memory Management  (https://pytorch.org/docs/stable/notes/cuda.html#environment-variables)
[default2]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1511, in _wrapped_call_impl
[default2]:    return self._call_impl(*args, **kwargs)
[default2]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1520, in _call_impl
[default2]:    return forward_call(*args, **kwargs)
[default2]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 597, in forward
[default2]:    output = self.o_proj(attention_output)
[default2]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1511, in _wrapped_call_impl
[default2]:    return self._call_impl(*args, **kwargs)
[default2]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1520, in _call_impl
[default2]:    return forward_call(*args, **kwargs)
[default2]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/tensor_parallel/nn.py", line 159, in forward
[default2]:    return row_linear(
[default2]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/tensor_parallel/functional.py", line 474, in row_linear
[default2]:    out = F.linear(input, weight, bias)
[default2]:torch.cuda.OutOfMemoryError: CUDA out of memory. Tried to allocate 128.00 MiB. GPU 2 has a total capacity of 79.33 GiB of which 95.94 MiB is free. Including non-PyTorch memory, this process has 79.22 GiB memory in use. Of the allocated memory 69.84 GiB is allocated by PyTorch, and 29.64 MiB is reserved by PyTorch but unallocated. If reserved but unallocated memory is large try setting PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True to avoid fragmentation.  See documentation for Memory Management  (https://pytorch.org/docs/stable/notes/cuda.html#environment-variables)
[default7]:Traceback (most recent call last):
[default7]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/run_train.py", line 237, in <module>
[default7]:    trainer.train(dataloader)
[default7]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/trainer.py", line 430, in train
[default7]:    outputs, loss_avg = self.training_step(dataloader=self.current_dataloader)
[default7]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/trainer.py", line 459, in training_step
[default7]:    outputs = self.pipeline_engine.train_batch_iter(
[default7]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/engine.py", line 187, in train_batch_iter
[default7]:    output = self.forward(context=context, state=state, micro_batch=micro_batch, model=model)
[default7]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/engine.py", line 44, in forward
[default7]:    output = model(**micro_batch)
[default7]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1511, in _wrapped_call_impl
[default7]:    return self._call_impl(*args, **kwargs)
[default7]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1520, in _call_impl
[default7]:    return forward_call(*args, **kwargs)
[default7]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 890, in forward
[default7]:    sharded_logits = self.model(
[default7]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1511, in _wrapped_call_impl
[default7]:    return self._call_impl(*args, **kwargs)
[default7]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1520, in _call_impl
[default7]:    return forward_call(*args, **kwargs)
[default7]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 764, in forward
[default7]:    return self.forward_with_hidden_states(input_ids=input_ids, input_mask=input_mask)[0]
[default7]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 780, in forward_with_hidden_states
[default7]:    hidden_encoder_states = encoder_block(**hidden_encoder_states)
[default7]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1511, in _wrapped_call_impl
[default7]:    return self._call_impl(*args, **kwargs)
[default7]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1520, in _call_impl
[default7]:    return forward_call(*args, **kwargs)
[default7]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/block.py", line 151, in forward
[default7]:    output = self.pp_block(**new_kwargs)
[default7]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1511, in _wrapped_call_impl
[default7]:    return self._call_impl(*args, **kwargs)
[default7]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1520, in _call_impl
[default7]:    return forward_call(*args, **kwargs)
[default7]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 636, in forward
[default7]:    hidden_states = self.mlp(hidden_states=hidden_states)["hidden_states"]
[default7]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1511, in _wrapped_call_impl
[default7]:    return self._call_impl(*args, **kwargs)
[default7]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1520, in _call_impl
[default7]:    return forward_call(*args, **kwargs)
[default7]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 171, in forward
[default7]:    hidden_states = self.down_proj(self.split_silu_mul(merged_states))
[default7]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1511, in _wrapped_call_impl
[default7]:    return self._call_impl(*args, **kwargs)
[default7]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1520, in _call_impl
[default7]:    return forward_call(*args, **kwargs)
[default7]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 127, in forward
[default7]:    return self.act(gate_states) * up_states
[default7]:torch.cuda.OutOfMemoryError: CUDA out of memory. Tried to allocate 32.00 MiB. GPU 7 has a total capacity of 79.33 GiB of which 31.94 MiB is free. Including non-PyTorch memory, this process has 79.28 GiB memory in use. Of the allocated memory 70.04 GiB is allocated by PyTorch, and 13.62 MiB is reserved by PyTorch but unallocated. If reserved but unallocated memory is large try setting PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True to avoid fragmentation.  See documentation for Memory Management  (https://pytorch.org/docs/stable/notes/cuda.html#environment-variables)
[default1]:Traceback (most recent call last):
[default1]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/run_train.py", line 237, in <module>
[default1]:    trainer.train(dataloader)
[default1]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/trainer.py", line 430, in train
[default1]:    outputs, loss_avg = self.training_step(dataloader=self.current_dataloader)
[default1]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/trainer.py", line 459, in training_step
[default1]:    outputs = self.pipeline_engine.train_batch_iter(
[default1]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/engine.py", line 187, in train_batch_iter
[default1]:    output = self.forward(context=context, state=state, micro_batch=micro_batch, model=model)
[default1]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/engine.py", line 44, in forward
[default1]:    output = model(**micro_batch)
[default1]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1511, in _wrapped_call_impl
[default1]:    return self._call_impl(*args, **kwargs)
[default1]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1520, in _call_impl
[default1]:    return forward_call(*args, **kwargs)
[default1]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 890, in forward
[default1]:    sharded_logits = self.model(
[default1]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1511, in _wrapped_call_impl
[default1]:    return self._call_impl(*args, **kwargs)
[default1]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1520, in _call_impl
[default1]:    return forward_call(*args, **kwargs)
[default1]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 764, in forward
[default1]:    return self.forward_with_hidden_states(input_ids=input_ids, input_mask=input_mask)[0]
[default1]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 780, in forward_with_hidden_states
[default1]:    hidden_encoder_states = encoder_block(**hidden_encoder_states)
[default1]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1511, in _wrapped_call_impl
[default1]:    return self._call_impl(*args, **kwargs)
[default1]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1520, in _call_impl
[default1]:    return forward_call(*args, **kwargs)
[default1]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/block.py", line 151, in forward
[default1]:    output = self.pp_block(**new_kwargs)
[default1]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1511, in _wrapped_call_impl
[default1]:    return self._call_impl(*args, **kwargs)
[default1]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1520, in _call_impl
[default1]:    return forward_call(*args, **kwargs)
[default1]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 636, in forward
[default1]:    hidden_states = self.mlp(hidden_states=hidden_states)["hidden_states"]
[default1]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1511, in _wrapped_call_impl
[default1]:    return self._call_impl(*args, **kwargs)
[default1]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1520, in _call_impl
[default1]:    return forward_call(*args, **kwargs)
[default1]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 171, in forward
[default1]:    hidden_states = self.down_proj(self.split_silu_mul(merged_states))
[default1]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1511, in _wrapped_call_impl
[default1]:    return self._call_impl(*args, **kwargs)
[default1]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1520, in _call_impl
[default1]:    return forward_call(*args, **kwargs)
[default1]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 127, in forward
[default1]:    return self.act(gate_states) * up_states
[default1]:torch.cuda.OutOfMemoryError: CUDA out of memory. Tried to allocate 32.00 MiB. GPU 1 has a total capacity of 79.33 GiB of which 13.94 MiB is free. Including non-PyTorch memory, this process has 79.30 GiB memory in use. Of the allocated memory 70.04 GiB is allocated by PyTorch, and 13.62 MiB is reserved by PyTorch but unallocated. If reserved but unallocated memory is large try setting PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True to avoid fragmentation.  See documentation for Memory Management  (https://pytorch.org/docs/stable/notes/cuda.html#environment-variables)
[default4]:    return forward_call(*args, **kwargs)
[default4]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/block.py", line 151, in forward
[default4]:    output = self.pp_block(**new_kwargs)
[default4]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1511, in _wrapped_call_impl
[default4]:    return self._call_impl(*args, **kwargs)
[default4]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1520, in _call_impl
[default4]:    return forward_call(*args, **kwargs)
[default4]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 630, in forward
[default4]:    output = self.attn(hidden_states=hidden_states, sequence_mask=sequence_mask)
[default4]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1511, in _wrapped_call_impl
[default4]:    return self._call_impl(*args, **kwargs)
[default4]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1520, in _call_impl
[default4]:    return forward_call(*args, **kwargs)
[default4]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 562, in forward
[default4]:    key_value_states = torch.cat([key_states.unsqueeze(0), value_states.unsqueeze(0)], dim=0)
[default4]:torch.cuda.OutOfMemoryError: CUDA out of memory. Tried to allocate 32.00 MiB. GPU 4 has a total capacity of 79.33 GiB of which 17.94 MiB is free. Including non-PyTorch memory, this process has 79.30 GiB memory in use. Of the allocated memory 69.78 GiB is allocated by PyTorch, and 12.14 MiB is reserved by PyTorch but unallocated. If reserved but unallocated memory is large try setting PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True to avoid fragmentation.  See documentation for Memory Management  (https://pytorch.org/docs/stable/notes/cuda.html#environment-variables)
[default0]:STAGE:2024-07-06 09:35:54 219090:219090 ActivityProfilerController.cpp:314] Completed Stage: Warm Up
[2024-07-06 09:35:59,397] torch.distributed.elastic.multiprocessing.api: [WARNING] Sending process 219090 closing signal SIGTERM
[2024-07-06 09:36:00,524] torch.distributed.elastic.multiprocessing.api: [ERROR] failed (exitcode: 1) local_rank: 1 (pid: 219091) of binary: /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10
Traceback (most recent call last):
  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/torchrun", line 8, in <module>
    sys.exit(main())
  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/errors/__init__.py", line 347, in wrapper
    return f(*args, **kwargs)
  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/run.py", line 812, in main
    run(args)
  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/run.py", line 803, in run
    elastic_launch(
  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/launcher/api.py", line 135, in __call__
    return launch_agent(self._config, self._entrypoint, list(args))
  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/launcher/api.py", line 268, in launch_agent
    raise ChildFailedError(
torch.distributed.elastic.multiprocessing.errors.ChildFailedError: 
============================================================
/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/run_train.py FAILED
------------------------------------------------------------
Failures:
[1]:
  time      : 2024-07-06_09:35:59
  host      : ip-26-0-160-103.ec2.internal
  rank      : 2 (local_rank: 2)
  exitcode  : 1 (pid: 219092)
  error_file: <N/A>
  traceback : To enable traceback see: https://pytorch.org/docs/stable/elastic/errors.html
[2]:
  time      : 2024-07-06_09:35:59
  host      : ip-26-0-160-103.ec2.internal
  rank      : 3 (local_rank: 3)
  exitcode  : 1 (pid: 219093)
  error_file: <N/A>
  traceback : To enable traceback see: https://pytorch.org/docs/stable/elastic/errors.html
[3]:
  time      : 2024-07-06_09:35:59
  host      : ip-26-0-160-103.ec2.internal
  rank      : 4 (local_rank: 4)
  exitcode  : 1 (pid: 219094)
  error_file: <N/A>
  traceback : To enable traceback see: https://pytorch.org/docs/stable/elastic/errors.html
[4]:
  time      : 2024-07-06_09:35:59
  host      : ip-26-0-160-103.ec2.internal
  rank      : 5 (local_rank: 5)
  exitcode  : 1 (pid: 219095)
  error_file: <N/A>
  traceback : To enable traceback see: https://pytorch.org/docs/stable/elastic/errors.html
[5]:
  time      : 2024-07-06_09:35:59
  host      : ip-26-0-160-103.ec2.internal
  rank      : 6 (local_rank: 6)
  exitcode  : 1 (pid: 219096)
  error_file: <N/A>
  traceback : To enable traceback see: https://pytorch.org/docs/stable/elastic/errors.html
[6]:
  time      : 2024-07-06_09:35:59
  host      : ip-26-0-160-103.ec2.internal
  rank      : 7 (local_rank: 7)
  exitcode  : 1 (pid: 219097)
  error_file: <N/A>
  traceback : To enable traceback see: https://pytorch.org/docs/stable/elastic/errors.html
------------------------------------------------------------
Root Cause (first observed failure):
[0]:
  time      : 2024-07-06_09:35:59
  host      : ip-26-0-160-103.ec2.internal
  rank      : 1 (local_rank: 1)
  exitcode  : 1 (pid: 219091)
  error_file: <N/A>
  traceback : To enable traceback see: https://pytorch.org/docs/stable/elastic/errors.html
============================================================
srun: error: ip-26-0-160-103: task 0: Exited with exit code 1
[2024-07-06 09:36:03,373] torch.distributed.elastic.rendezvous.dynamic_rendezvous: [WARNING] The node 'ip-26-0-163-147.ec2.internal_2032455_0' has failed to send a keep-alive heartbeat to the rendezvous 'none' due to an error of type RendezvousConnectionError.
[2024-07-06 09:36:04,111] torch.distributed.elastic.rendezvous.dynamic_rendezvous: [WARNING] The node 'ip-26-0-172-142.ec2.internal_3936756_0' has failed to send a keep-alive heartbeat to the rendezvous 'none' due to an error of type RendezvousConnectionError.
[2024-07-06 09:36:04,202] torch.distributed.elastic.rendezvous.dynamic_rendezvous: [WARNING] The node 'ip-26-0-161-138.ec2.internal_1422179_0' has failed to send a keep-alive heartbeat to the rendezvous 'none' due to an error of type RendezvousConnectionError.
[2024-07-06 09:36:04,220] torch.distributed.elastic.rendezvous.dynamic_rendezvous: [WARNING] The node 'ip-26-0-165-213.ec2.internal_159341_0' has failed to send a keep-alive heartbeat to the rendezvous 'none' due to an error of type RendezvousConnectionError.
[2024-07-06 09:36:04,309] torch.distributed.elastic.rendezvous.dynamic_rendezvous: [WARNING] The node 'ip-26-0-172-147.ec2.internal_1333357_0' has failed to send a keep-alive heartbeat to the rendezvous 'none' due to an error of type RendezvousConnectionError.
[2024-07-06 09:36:04,332] torch.distributed.elastic.rendezvous.dynamic_rendezvous: [WARNING] The node 'ip-26-0-166-15.ec2.internal_83512_0' has failed to send a keep-alive heartbeat to the rendezvous 'none' due to an error of type RendezvousConnectionError.
[2024-07-06 09:36:04,359] torch.distributed.elastic.rendezvous.dynamic_rendezvous: [WARNING] The node 'ip-26-0-163-58.ec2.internal_1205485_0' has failed to send a keep-alive heartbeat to the rendezvous 'none' due to an error of type RendezvousConnectionError.
[2024-07-06 09:36:04,392] torch.distributed.elastic.multiprocessing.api: [WARNING] Sending process 1422249 closing signal SIGTERM
[2024-07-06 09:36:04,392] torch.distributed.elastic.multiprocessing.api: [WARNING] Sending process 1422250 closing signal SIGTERM
[2024-07-06 09:36:04,394] torch.distributed.elastic.multiprocessing.api: [WARNING] Sending process 1422251 closing signal SIGTERM
[2024-07-06 09:36:04,395] torch.distributed.elastic.multiprocessing.api: [WARNING] Sending process 1205555 closing signal SIGTERM
[2024-07-06 09:36:04,395] torch.distributed.elastic.multiprocessing.api: [WARNING] Sending process 1205556 closing signal SIGTERM
[2024-07-06 09:36:04,394] torch.distributed.elastic.multiprocessing.api: [WARNING] Sending process 1422252 closing signal SIGTERM
[2024-07-06 09:36:04,395] torch.distributed.elastic.multiprocessing.api: [WARNING] Sending process 1205557 closing signal SIGTERM
[2024-07-06 09:36:04,394] torch.distributed.elastic.multiprocessing.api: [WARNING] Sending process 1422253 closing signal SIGTERM
[2024-07-06 09:36:04,395] torch.distributed.elastic.multiprocessing.api: [WARNING] Sending process 1422254 closing signal SIGTERM
[2024-07-06 09:36:04,395] torch.distributed.elastic.multiprocessing.api: [WARNING] Sending process 1422255 closing signal SIGTERM
[2024-07-06 09:36:04,395] torch.distributed.elastic.multiprocessing.api: [WARNING] Sending process 1333427 closing signal SIGTERM
[2024-07-06 09:36:04,396] torch.distributed.elastic.multiprocessing.api: [WARNING] Sending process 1333428 closing signal SIGTERM
[2024-07-06 09:36:04,396] torch.distributed.elastic.multiprocessing.api: [WARNING] Sending process 1422256 closing signal SIGTERM
[2024-07-06 09:36:04,397] torch.distributed.elastic.multiprocessing.api: [WARNING] Sending process 1205558 closing signal SIGTERM
[2024-07-06 09:36:04,396] torch.distributed.elastic.multiprocessing.api: [WARNING] Sending process 1333429 closing signal SIGTERM
[2024-07-06 09:36:04,396] torch.distributed.elastic.multiprocessing.api: [WARNING] Sending process 159411 closing signal SIGTERM
[2024-07-06 09:36:04,397] torch.distributed.elastic.multiprocessing.api: [WARNING] Sending process 159412 closing signal SIGTERM
[2024-07-06 09:36:04,397] torch.distributed.elastic.multiprocessing.api: [WARNING] Sending process 1333430 closing signal SIGTERM
[2024-07-06 09:36:04,398] torch.distributed.elastic.multiprocessing.api: [WARNING] Sending process 1205559 closing signal SIGTERM
[2024-07-06 09:36:04,398] torch.distributed.elastic.multiprocessing.api: [WARNING] Sending process 1333431 closing signal SIGTERM
[2024-07-06 09:36:04,399] torch.distributed.elastic.multiprocessing.api: [WARNING] Sending process 1205560 closing signal SIGTERM
[2024-07-06 09:36:04,398] torch.distributed.elastic.multiprocessing.api: [WARNING] Sending process 159413 closing signal SIGTERM
[2024-07-06 09:36:04,399] torch.distributed.elastic.multiprocessing.api: [WARNING] Sending process 1205561 closing signal SIGTERM
[2024-07-06 09:36:04,400] torch.distributed.elastic.multiprocessing.api: [WARNING] Sending process 1205562 closing signal SIGTERM
[2024-07-06 09:36:04,400] torch.distributed.elastic.multiprocessing.api: [WARNING] Sending process 3936826 closing signal SIGTERM
[2024-07-06 09:36:04,400] torch.distributed.elastic.multiprocessing.api: [WARNING] Sending process 3936827 closing signal SIGTERM
[2024-07-06 09:36:04,399] torch.distributed.elastic.multiprocessing.api: [WARNING] Sending process 159414 closing signal SIGTERM
[2024-07-06 09:36:04,401] torch.distributed.elastic.multiprocessing.api: [WARNING] Sending process 3936828 closing signal SIGTERM
[2024-07-06 09:36:04,401] torch.distributed.elastic.multiprocessing.api: [WARNING] Sending process 1333432 closing signal SIGTERM
[2024-07-06 09:36:04,401] torch.distributed.elastic.multiprocessing.api: [WARNING] Sending process 159415 closing signal SIGTERM
[2024-07-06 09:36:04,401] torch.distributed.elastic.multiprocessing.api: [WARNING] Sending process 159416 closing signal SIGTERM
[2024-07-06 09:36:04,402] torch.distributed.elastic.multiprocessing.api: [WARNING] Sending process 3936829 closing signal SIGTERM
[2024-07-06 09:36:04,402] torch.distributed.elastic.multiprocessing.api: [WARNING] Sending process 159417 closing signal SIGTERM
[2024-07-06 09:36:04,404] torch.distributed.elastic.multiprocessing.api: [WARNING] Sending process 3936830 closing signal SIGTERM
[2024-07-06 09:36:04,403] torch.distributed.elastic.multiprocessing.api: [WARNING] Sending process 2032525 closing signal SIGTERM
[2024-07-06 09:36:04,403] torch.distributed.elastic.multiprocessing.api: [WARNING] Sending process 2032526 closing signal SIGTERM
[2024-07-06 09:36:04,403] torch.distributed.elastic.multiprocessing.api: [WARNING] Sending process 159418 closing signal SIGTERM
[2024-07-06 09:36:04,404] torch.distributed.elastic.multiprocessing.api: [WARNING] Sending process 3936831 closing signal SIGTERM
[2024-07-06 09:36:04,405] torch.distributed.elastic.multiprocessing.api: [WARNING] Sending process 3936832 closing signal SIGTERM
[2024-07-06 09:36:04,406] torch.distributed.elastic.multiprocessing.api: [WARNING] Sending process 3936833 closing signal SIGTERM
[2024-07-06 09:36:04,402] torch.distributed.elastic.multiprocessing.api: [WARNING] Sending process 1333433 closing signal SIGTERM
[2024-07-06 09:36:04,402] torch.distributed.elastic.multiprocessing.api: [WARNING] Sending process 1333434 closing signal SIGTERM
[2024-07-06 09:36:04,405] torch.distributed.elastic.multiprocessing.api: [WARNING] Sending process 2032527 closing signal SIGTERM
[2024-07-06 09:36:04,406] torch.distributed.elastic.multiprocessing.api: [WARNING] Sending process 2032528 closing signal SIGTERM
[2024-07-06 09:36:04,407] torch.distributed.elastic.multiprocessing.api: [WARNING] Sending process 2032529 closing signal SIGTERM
[2024-07-06 09:36:04,408] torch.distributed.elastic.multiprocessing.api: [WARNING] Sending process 83583 closing signal SIGTERM
[2024-07-06 09:36:04,409] torch.distributed.elastic.multiprocessing.api: [WARNING] Sending process 83584 closing signal SIGTERM
[2024-07-06 09:36:04,409] torch.distributed.elastic.multiprocessing.api: [WARNING] Sending process 2032530 closing signal SIGTERM
[2024-07-06 09:36:04,409] torch.distributed.elastic.multiprocessing.api: [WARNING] Sending process 2032531 closing signal SIGTERM
[2024-07-06 09:36:04,410] torch.distributed.elastic.multiprocessing.api: [WARNING] Sending process 2032532 closing signal SIGTERM
[2024-07-06 09:36:04,411] torch.distributed.elastic.multiprocessing.api: [WARNING] Sending process 83585 closing signal SIGTERM
[2024-07-06 09:36:04,412] torch.distributed.elastic.multiprocessing.api: [WARNING] Sending process 83586 closing signal SIGTERM
[2024-07-06 09:36:04,412] torch.distributed.elastic.multiprocessing.api: [WARNING] Sending process 83587 closing signal SIGTERM
[2024-07-06 09:36:04,414] torch.distributed.elastic.multiprocessing.api: [WARNING] Sending process 83588 closing signal SIGTERM
[2024-07-06 09:36:04,414] torch.distributed.elastic.multiprocessing.api: [WARNING] Sending process 83589 closing signal SIGTERM
[2024-07-06 09:36:04,415] torch.distributed.elastic.multiprocessing.api: [WARNING] Sending process 83590 closing signal SIGTERM
[2024-07-06 09:36:07,938] torch.distributed.elastic.rendezvous.dynamic_rendezvous: [WARNING] The node 'ip-26-0-172-147.ec2.internal_1333357_0' has failed to shutdown the rendezvous 'none' due to an error of type RendezvousConnectionError.
Traceback (most recent call last):
  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/elastic/rendezvous/c10d_rendezvous_backend.py", line 113, in _call_store
    return getattr(self._store, store_op)(*args, **kwargs)
torch.distributed.DistNetworkError: Broken pipe

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/torchrun", line 8, in <module>
    sys.exit(main())
  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/errors/__init__.py", line 347, in wrapper
    return f(*args, **kwargs)
  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/run.py", line 812, in main
    run(args)
  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/run.py", line 803, in run
    elastic_launch(
  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/launcher/api.py", line 135, in __call__
    return launch_agent(self._config, self._entrypoint, list(args))
  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/launcher/api.py", line 259, in launch_agent
    result = agent.run()
  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/elastic/metrics/api.py", line 123, in wrapper
    result = f(*args, **kwargs)
  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/elastic/agent/server/api.py", line 727, in run
    result = self._invoke_run(role)
  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/elastic/agent/server/api.py", line 900, in _invoke_run
    num_nodes_waiting = rdzv_handler.num_nodes_waiting()
  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/elastic/rendezvous/dynamic_rendezvous.py", line 1083, in num_nodes_waiting
    self._state_holder.sync()
  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/elastic/rendezvous/dynamic_rendezvous.py", line 409, in sync
    get_response = self._backend.get_state()
  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/elastic/rendezvous/c10d_rendezvous_backend.py", line 73, in get_state
    base64_state: bytes = self._call_store("get", self._key)
  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/elastic/rendezvous/c10d_rendezvous_backend.py", line 115, in _call_store
    raise RendezvousConnectionError(
torch.distributed.elastic.rendezvous.api.RendezvousConnectionError: The connection to the C10d store has failed. See inner exception for details.
srun: error: ip-26-0-172-147: task 7: Exited with exit code 1
[2024-07-06 09:36:08,378] torch.distributed.elastic.rendezvous.dynamic_rendezvous: [WARNING] The node 'ip-26-0-163-147.ec2.internal_2032455_0' has failed to send a keep-alive heartbeat to the rendezvous 'none' due to an error of type RendezvousConnectionError.
[2024-07-06 09:36:08,639] torch.distributed.elastic.rendezvous.dynamic_rendezvous: [WARNING] The node 'ip-26-0-163-147.ec2.internal_2032455_0' has failed to shutdown the rendezvous 'none' due to an error of type RendezvousConnectionError.
Traceback (most recent call last):
  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/elastic/rendezvous/c10d_rendezvous_backend.py", line 113, in _call_store
    return getattr(self._store, store_op)(*args, **kwargs)
torch.distributed.DistNetworkError: Broken pipe

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/torchrun", line 8, in <module>
    sys.exit(main())
  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/errors/__init__.py", line 347, in wrapper
    return f(*args, **kwargs)
  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/run.py", line 812, in main
    run(args)
  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/run.py", line 803, in run
    elastic_launch(
  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/launcher/api.py", line 135, in __call__
    return launch_agent(self._config, self._entrypoint, list(args))
  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/launcher/api.py", line 259, in launch_agent
    result = agent.run()
  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/elastic/metrics/api.py", line 123, in wrapper
    result = f(*args, **kwargs)
  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/elastic/agent/server/api.py", line 727, in run
    result = self._invoke_run(role)
  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/elastic/agent/server/api.py", line 900, in _invoke_run
    num_nodes_waiting = rdzv_handler.num_nodes_waiting()
  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/elastic/rendezvous/dynamic_rendezvous.py", line 1083, in num_nodes_waiting
    self._state_holder.sync()
  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/elastic/rendezvous/dynamic_rendezvous.py", line 409, in sync
    get_response = self._backend.get_state()
  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/elastic/rendezvous/c10d_rendezvous_backend.py", line 73, in get_state
    base64_state: bytes = self._call_store("get", self._key)
  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/elastic/rendezvous/c10d_rendezvous_backend.py", line 115, in _call_store
    raise RendezvousConnectionError(
torch.distributed.elastic.rendezvous.api.RendezvousConnectionError: The connection to the C10d store has failed. See inner exception for details.
srun: error: ip-26-0-163-147: task 3: Exited with exit code 1
[2024-07-06 09:36:08,942] torch.distributed.elastic.rendezvous.dynamic_rendezvous: [WARNING] The node 'ip-26-0-161-138.ec2.internal_1422179_0' has failed to shutdown the rendezvous 'none' due to an error of type RendezvousConnectionError.
Traceback (most recent call last):
  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/elastic/rendezvous/c10d_rendezvous_backend.py", line 113, in _call_store
    return getattr(self._store, store_op)(*args, **kwargs)
torch.distributed.DistNetworkError: Broken pipe

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/torchrun", line 8, in <module>
    sys.exit(main())
  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/errors/__init__.py", line 347, in wrapper
    return f(*args, **kwargs)
  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/run.py", line 812, in main
    run(args)
  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/run.py", line 803, in run
    elastic_launch(
  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/launcher/api.py", line 135, in __call__
    return launch_agent(self._config, self._entrypoint, list(args))
  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/launcher/api.py", line 259, in launch_agent
    result = agent.run()
  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/elastic/metrics/api.py", line 123, in wrapper
    result = f(*args, **kwargs)
  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/elastic/agent/server/api.py", line 727, in run
    result = self._invoke_run(role)
  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/elastic/agent/server/api.py", line 900, in _invoke_run
    num_nodes_waiting = rdzv_handler.num_nodes_waiting()
  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/elastic/rendezvous/dynamic_rendezvous.py", line 1083, in num_nodes_waiting
    self._state_holder.sync()
  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/elastic/rendezvous/dynamic_rendezvous.py", line 409, in sync
    get_response = self._backend.get_state()
  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/elastic/rendezvous/c10d_rendezvous_backend.py", line 73, in get_state
    base64_state: bytes = self._call_store("get", self._key)
  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/elastic/rendezvous/c10d_rendezvous_backend.py", line 115, in _call_store
    raise RendezvousConnectionError(
torch.distributed.elastic.rendezvous.api.RendezvousConnectionError: The connection to the C10d store has failed. See inner exception for details.
[2024-07-06 09:36:09,042] torch.distributed.elastic.rendezvous.dynamic_rendezvous: [WARNING] The node 'ip-26-0-172-142.ec2.internal_3936756_0' has failed to shutdown the rendezvous 'none' due to an error of type RendezvousConnectionError.
Traceback (most recent call last):
  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/elastic/rendezvous/c10d_rendezvous_backend.py", line 113, in _call_store
    return getattr(self._store, store_op)(*args, **kwargs)
torch.distributed.DistNetworkError: Broken pipe

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/torchrun", line 8, in <module>
    sys.exit(main())
  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/errors/__init__.py", line 347, in wrapper
    return f(*args, **kwargs)
  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/run.py", line 812, in main
    run(args)
  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/run.py", line 803, in run
    elastic_launch(
  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/launcher/api.py", line 135, in __call__
    return launch_agent(self._config, self._entrypoint, list(args))
  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/launcher/api.py", line 259, in launch_agent
    result = agent.run()
  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/elastic/metrics/api.py", line 123, in wrapper
    result = f(*args, **kwargs)
  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/elastic/agent/server/api.py", line 727, in run
    result = self._invoke_run(role)
  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/elastic/agent/server/api.py", line 900, in _invoke_run
    num_nodes_waiting = rdzv_handler.num_nodes_waiting()
  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/elastic/rendezvous/dynamic_rendezvous.py", line 1083, in num_nodes_waiting
    self._state_holder.sync()
  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/elastic/rendezvous/dynamic_rendezvous.py", line 409, in sync
    get_response = self._backend.get_state()
[2024-07-06 09:36:09,047] torch.distributed.elastic.rendezvous.dynamic_rendezvous: [WARNING] The node 'ip-26-0-165-213.ec2.internal_159341_0' has failed to shutdown the rendezvous 'none' due to an error of type RendezvousConnectionError.
  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/elastic/rendezvous/c10d_rendezvous_backend.py", line 73, in get_state
Traceback (most recent call last):
  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/elastic/rendezvous/c10d_rendezvous_backend.py", line 113, in _call_store
    base64_state: bytes = self._call_store("get", self._key)
    return getattr(self._store, store_op)(*args, **kwargs)
  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/elastic/rendezvous/c10d_rendezvous_backend.py", line 115, in _call_store
torch.distributed.DistNetworkError: Broken pipe

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
    raise RendezvousConnectionError(
  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/torchrun", line 8, in <module>
torch.distributed.elastic.rendezvous.api.RendezvousConnectionError: The connection to the C10d store has failed. See inner exception for details.
    sys.exit(main())
  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/errors/__init__.py", line 347, in wrapper
    return f(*args, **kwargs)
  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/run.py", line 812, in main
    run(args)
  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/run.py", line 803, in run
    elastic_launch(
  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/launcher/api.py", line 135, in __call__
    return launch_agent(self._config, self._entrypoint, list(args))
  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/launcher/api.py", line 259, in launch_agent
    result = agent.run()
  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/elastic/metrics/api.py", line 123, in wrapper
    result = f(*args, **kwargs)
  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/elastic/agent/server/api.py", line 727, in run
    result = self._invoke_run(role)
  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/elastic/agent/server/api.py", line 900, in _invoke_run
    num_nodes_waiting = rdzv_handler.num_nodes_waiting()
  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/elastic/rendezvous/dynamic_rendezvous.py", line 1083, in num_nodes_waiting
    self._state_holder.sync()
  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/elastic/rendezvous/dynamic_rendezvous.py", line 409, in sync
    get_response = self._backend.get_state()
  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/elastic/rendezvous/c10d_rendezvous_backend.py", line 73, in get_state
    base64_state: bytes = self._call_store("get", self._key)
  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/elastic/rendezvous/c10d_rendezvous_backend.py", line 115, in _call_store
    raise RendezvousConnectionError(
torch.distributed.elastic.rendezvous.api.RendezvousConnectionError: The connection to the C10d store has failed. See inner exception for details.
srun: error: ip-26-0-161-138: task 1: Exited with exit code 1
srun: error: ip-26-0-172-142: task 6: Exited with exit code 1
[2024-07-06 09:36:09,336] torch.distributed.elastic.rendezvous.dynamic_rendezvous: [WARNING] The node 'ip-26-0-163-58.ec2.internal_1205485_0' has failed to shutdown the rendezvous 'none' due to an error of type RendezvousConnectionError.
Traceback (most recent call last):
  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/elastic/rendezvous/c10d_rendezvous_backend.py", line 113, in _call_store
    return getattr(self._store, store_op)(*args, **kwargs)
torch.distributed.DistNetworkError: Broken pipe

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/torchrun", line 8, in <module>
    sys.exit(main())
  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/errors/__init__.py", line 347, in wrapper
    return f(*args, **kwargs)
  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/run.py", line 812, in main
    run(args)
  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/run.py", line 803, in run
    elastic_launch(
  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/launcher/api.py", line 135, in __call__
[2024-07-06 09:36:09,337] torch.distributed.elastic.rendezvous.dynamic_rendezvous: [WARNING] The node 'ip-26-0-166-15.ec2.internal_83512_0' has failed to send a keep-alive heartbeat to the rendezvous 'none' due to an error of type RendezvousConnectionError.
    return launch_agent(self._config, self._entrypoint, list(args))
  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/launcher/api.py", line 259, in launch_agent
    result = agent.run()
  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/elastic/metrics/api.py", line 123, in wrapper
    result = f(*args, **kwargs)
  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/elastic/agent/server/api.py", line 727, in run
    result = self._invoke_run(role)
  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/elastic/agent/server/api.py", line 900, in _invoke_run
    num_nodes_waiting = rdzv_handler.num_nodes_waiting()
  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/elastic/rendezvous/dynamic_rendezvous.py", line 1083, in num_nodes_waiting
    self._state_holder.sync()
  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/elastic/rendezvous/dynamic_rendezvous.py", line 409, in sync
    get_response = self._backend.get_state()
  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/elastic/rendezvous/c10d_rendezvous_backend.py", line 73, in get_state
    base64_state: bytes = self._call_store("get", self._key)
  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/elastic/rendezvous/c10d_rendezvous_backend.py", line 115, in _call_store
    raise RendezvousConnectionError(
torch.distributed.elastic.rendezvous.api.RendezvousConnectionError: The connection to the C10d store has failed. See inner exception for details.
[2024-07-06 09:36:09,350] torch.distributed.elastic.rendezvous.dynamic_rendezvous: [WARNING] The node 'ip-26-0-166-15.ec2.internal_83512_0' has failed to shutdown the rendezvous 'none' due to an error of type RendezvousConnectionError.
Traceback (most recent call last):
  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/elastic/rendezvous/c10d_rendezvous_backend.py", line 113, in _call_store
    return getattr(self._store, store_op)(*args, **kwargs)
torch.distributed.DistNetworkError: Broken pipe

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/torchrun", line 8, in <module>
    sys.exit(main())
  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/errors/__init__.py", line 347, in wrapper
    return f(*args, **kwargs)
  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/run.py", line 812, in main
    run(args)
  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/run.py", line 803, in run
    elastic_launch(
  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/launcher/api.py", line 135, in __call__
    return launch_agent(self._config, self._entrypoint, list(args))
  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/launcher/api.py", line 259, in launch_agent
    result = agent.run()
  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/elastic/metrics/api.py", line 123, in wrapper
    result = f(*args, **kwargs)
  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/elastic/agent/server/api.py", line 727, in run
    result = self._invoke_run(role)
  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/elastic/agent/server/api.py", line 900, in _invoke_run
    num_nodes_waiting = rdzv_handler.num_nodes_waiting()
  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/elastic/rendezvous/dynamic_rendezvous.py", line 1083, in num_nodes_waiting
    self._state_holder.sync()
  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/elastic/rendezvous/dynamic_rendezvous.py", line 409, in sync
    get_response = self._backend.get_state()
  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/elastic/rendezvous/c10d_rendezvous_backend.py", line 73, in get_state
    base64_state: bytes = self._call_store("get", self._key)
  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/elastic/rendezvous/c10d_rendezvous_backend.py", line 115, in _call_store
    raise RendezvousConnectionError(
torch.distributed.elastic.rendezvous.api.RendezvousConnectionError: The connection to the C10d store has failed. See inner exception for details.
srun: error: ip-26-0-165-213: task 4: Exited with exit code 1
srun: error: ip-26-0-163-58: task 2: Exited with exit code 1
srun: error: ip-26-0-166-15: task 5: Exited with exit code 1
Consider using `hf_transfer` for faster uploads. This solution comes with some limitations. See https://huggingface.co/docs/huggingface_hub/hf_transfer for more details.